Abstract: The recent media focus on Smart City services, particularly ride sharing, that provide ordinary users with the ability to advertise their resources has highlighted society’s need for transparent and accountable systems. Current systems offer little transparency behind their processes that claim to provide accountability to and for their users. To address such a concern, some applications provide a static, textual description of the automated algorithms used, with a view to promote transparency. However, this is not sufficient to inform users exactly how information is derived. These descriptions can be enhanced by explaining the actual execution of the algorithm, the data it operated on, and the parameters it was configured with. Such descriptions about a system’s execution and its information flow can be expressed using PROV, a standardised provenance data model. However, given its generic and domain-agnostic nature, PROV only provides limited information about the relationship between provenance elements. Combined with semantic information, a PROV instance becomes a rich resource, which can be exploited to provide users with understandable accounts of automated processes, thereby promoting transparency and accountability. Thus, this paper contributes, a vocabulary for Smart City resource sharing applications, an architecture for accountable systems, and a set of use cases that demonstrate and quantify how the semantics enrich an account in a ride share scenario.

Citation: Heather Packer, Dimitris Diochnos, Michael Rovatsos, Ya’akov Gal, Luc Moreau, Semantics and Provenance for Accountable Smart City Applications, The Role of Semantics in Smart Cities, Semantic Web Journal special issue, 2014.

Download: http://bit.ly/2jcTK9B

Abstract: Collaborative localization is the computation of improved spatial coordinates in mobile agents based on their physical meetings in a pedestrian dead reckoning (PDR) system. Upon meeting the agents can exchange information about their subjective position and update it based on a simple algorithm. We show in a simulation model that the localization error diverges unless this algorithm is introduced in which case it remains bounded. We consider collaborative localization as an example of broader incremental knowledge fusion and discuss its various implications such as the importance of well-informed agents.

Citation: Kampis, G. and Lukowicz, P. (2014): Collaborative Localization as a Paradigm for Incremental Knowledge Fusion, 5th IEEE CogInfoCom 2014 Conference

Download: http://bit.ly/2ilkZKT

Abstract: In this paper we present a novel approach to multiagent planning in domains with concurrent actions and associated concurrent action constraints. In these domains, we associate the actions of individual agents with subsets of objects, which allows for a transformation of the problems into single-agent planning problems that are considerably easier to solve. The transformation forces agents to select joint actions associated with a single subset of objects at a time, and ensures that the concurrency constraints on this subset are satisfied. Joint actions are serialised such that each agent performs their part of the action separately. The number of actions in the resulting single-agent planning problem turns out to be manageable in many real-world domains, thus allowing the problem to be solved efficiently using a standard single-agent planner. We also describe a cost-optimal algorithm for compressing the resulting plan, i.e. merging individual actions in order to reduce the total number of joint actions. Results show that our approach can handle large problems that are impossible to solve for most multiagent planners.

Citation: M. Crosby, A. Jonsson, M. Rovatsos. A Single-Agent Approach to Multiagent Planning. Proceedings of the 21st European Conference on Artificial Intelligence (ECAI 2014), Prague, Czech Republic, August 18-22, 2014.

Download: http://bit.ly/2jcNwGT

Abstract: Novel web-based socio-technical systems require incentives for efficient management and motivation of human workers taking part in complex collaborations. Incentive management techniques used in existing crowdsourcing platforms are not suitable for intellectually-challenging tasks; platform-specific solutions prevent both workers from comparing working conditions across different platforms as well as platform owners from attracting skilled workers. In this paper we present PRINGL, a domain-specific language for programming complex incentive strategies. It promotes re-use of proven incentive logic and allows composing of complex incentives suitable for novel types of socio-technical systems. We illustrate its applicability and expressiveness and discuss its properties and limitations.

Citation: Ognjen Scekic, Hong-Linh Truong, Schahram Dustdar, “Managing Incentives in Social Computing Systems with PRINGL”, 15th Intl. Conf. on Web Information Systems Engineering (WISE), Thessaloniki, Greece, October, 2014.

Download: http://bit.ly/2jJrT1B

Abstract: Collective adaptive systems (CASs) have been researched intensively since many years. However, the recent emerging developments and advanced models in service-oriented computing, cloud computing and human computation have fostered several new forms of CASs. Among them, Hybrid and Diversity-aware CASs (HDA-CASs) characterize new types of CASs in which a collective is composed of hybrid machines and humans that collaborate together with different complementary roles. This emerging HDA-CAS poses several research challenges in terms of programming, management and provisioning. In this paper, we investigate the main issues in programming HDA-CASs. First, we analyze context characterizing HDA-CASs. Second, we propose to use the concept of hybrid compute units to implement HDA-CASs that can be elastic. We call this type of HDA-CASs h2h2 CAS (Hybrid Compute Unit-based HDA-CAS). We then discuss a meta-view of h2h2 CAS that describes a h2h2 CAS program. We analyze and present program features for h2h2 CAS in four main different contexts.

Citation: Hong-Linh Truong, Schahram Dustdar, “Context-aware Programming for Hybrid and Diversity-aware Collective Adaptive Systems”, Springer, International Workshop on Business Processes in Collective Adaptive Systems (BPCAS 2014), 12th Intl. Conf. on Business Process Management (BPM14), Eindhoven, The Netherlands, September 7-12, 2014

Download: http://bit.ly/2ipAi8F

Abstract: In this work, we show how a smart-phone worn unobtrusively in a nurses coat pocket can be used to document the patient care activities performed during a regular morning routine. The main contribution is to show how, taking into account certain domain specific boundary conditions, a single sensor node worn in such an (from the sensing point of view) unfavorable location can still recognize complex, sometimes subtle activities. We evaluate our approach in a large real life dataset from day to day hospital operation. In total, 4 runs of patient care per day were collected for 14 days at a geriatric ward and annotated in high detail by following the performing nurses for the entire duration. This amounts to over 800 hours of sensor data including acceleration, gyroscope, compass, wifi and sound annotated with groundtruth at less than 1min resolution.

Citation: Gernot Bahle, Agnes Gruenerbl, Enrico Bignotti, Mattia Zeni, Fausto Giunchiglia and Paul Lukowicz (2014): “Recognizing Hospital Care Activities with a Pocket Worn Smartphone”, 6th International Conference on Mobile Computing, Applications and Services (MobiCASE 2014)

Download: http://bit.ly/2jcB3mo

Abstract: Digital societies increasingly rely on secure communication between parties. Certificate enrollment protocols are used by certificate authorities to issue public key certificates to clients. Key agreement protocols, such as Diffie-Hellman, are used to compute secret keys, using public keys as input, for establishing secure communication channels. Whenever the keys are generated by clients, the bootstrap process requires either (a) an out-of-band verification for certification of keys when those are generated by the clients themselves, or (b) a trusted server to generate both the public and secret parameters. This paper presents a novel constrained key agreement protocol, built upon a constrained Diffie-Hellman, which is used to generate a secure public-private key pair, and to set up a certification environment without disclosing the private keys. In this way, the servers can guarantee that the generated key parameters are safe, and the clients do not disclose any secret information to the servers.

Citation: F{\’a}bio Borges and Leonardo A. Martucci and Filipe Beato and and Max M{\”u}hlh{\”a}user (2014). Secure and Privacy-Friendly Public Key Generation and Certification. In Proceedings of the 13th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 24–26 September, Beijing, China, TrustCom 2014.

Download: http://bit.ly/2j4irD0

Abstract: Privacy-enhancing technologies for the Smart Grid usually address either the consolidation of users’ energy consumption or the verification of billing information. The goal of this paper is to introduce iKUP, a protocol that addresses both problems simultaneously. iKUP is an efficient privacy-enhancing protocol based on DC-Nets and Elliptic Curve Cryptography as Commitment. It covers the entire cycle of power provisioning, consumption, billing, and verification. iKUP allows: (i) utility providers to obtain a consolidated energy consumption value that relates to the consumption of a user set, (ii) utility providers to verify the correctness of this consolidated value, and (iii) the verification of the correctness of the billing information by both utility providers and users. iKUP prevents utility providers from identifying individual contributions to the consolidated value and, therefore, protects the users’ privacy. The analytical performance evaluation of iKUP is validated through simulation using as input a real-world data set with over 157 million measurements collected from 6,345 smart meters. Our results show that iKUP has a worse performance than other protocols in aggregation and decryption, which are operations that happen only once per round of measurements and, thus, have a low impact in the total protocol performance. iKUP heavily outperforms other protocols in encryption, which is the most demanded cryptographic function, has the highest impact on the overall protocol performance, and it is executed in the smart meters.

Citation: F{\’a}bio Borges and Leonardo A. Martucci (2014). {iKUP} Keeps Users’ Privacy in the Smart Grid. In Proceedings of the IEEE Conference on Communications and Network Security (CNS 2014), 29–31 Oct, San Francisco, CA, USA.

Download: http://bit.ly/2iKIKgv

Abstract: Corruption frequently occurs in many aspects of multi-party interaction between private agencies and government employees. Past works studying corruption in a lab context have explicitly included covert or illegal activities in participants’ strategy space or have relied on surveys like the Corruption Perception Index (CPI). This paper studies corruption in ecologically realistic settings in which corruption is not suggested to the players a priori but evolves during repeated interaction. We ran studies involving hundreds of subjects in three countries: China, Israel, and the United States. Subjects interacted using a four-player board game in which three bidders compete to win contracts by submitting bids in repeated auctions, and a single auctioneer determines the winner of each auction. The winning bid was paid to an external “government” entity, and was not distributed among the players. The game logs were analyzed posthoc for cases in which the auctioneer was bribed to choose a bidder who did not submit the highest bid. We found that although China exhibited the highest corruption level of the three countries, there were surprisingly more cases of corruption in the U.S. than in Israel, despite the higher PCI in Israel as compared to the U.S. We also found that bribes in the U.S. were at times excessively high, resulting in bribing players not being able to complete their winning contracts. We were able to predict the occurrence of corruption in the game using machine learning. The significance of this work is in providing a novel paradigm for investigating covert activities in the lab without priming subjects, and it represents a first step in the design of intelligent agents for detecting and reducing corruption activities in such settings.

Citation: Ya’akov Gal, Avi Rosenfeld, Sarit Kraus, Michele Gelfand, Bo An and Jun Lin. A new paradigm for the study of corruption across cultures. International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP), Maryland, MD, April 2014.

Download: http://bit.ly/2ijGQCm

Abstract: Crowdsourcing is generally used for tasks with minimal coordination, providing limited support for dynamic reconfiguration. Modern systems, exemplified by social machines, are subject to continual flux in both the client and development communities and their needs. To support crowd sourcing of open-ended development, systems must dynamically integrate human creativity with machine support. While workflows can be used to handle structured, predictable processes, they are less suitable for social machine development and its attendant uncertainty. We present models and techniques for coordination of human workers in crowd sourced software development environments. We combine the Social Compute Unit—a model of ad-hoc human worker teams—with versatile coordination protocols expressed in the Lightweight Social Calculus. This allows us to combine coordination and quality constraints with dynamic assessments of end-user desires, dynamically discovering and applying development protocols.

Citation: Dave Murray-Rust, Ognjen Scekic, Hong-Linh Truong, Dave Robertson and Schahram Dustdar. A Collaboration Model for Community-Based Software Development with Social Machines. 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, 22-25 Oct, Miami, FL, USA, 2014.

Download: http://bit.ly/2jaHx55

Abstract: We report work in progress on the role of models in the formation and maintenance of collectives in Hybrid Diversity-Aware Collective Adaptive Systems (HDA-CASs). HDA-CASs utilize hybrid computations involving machines and humans operating in collectives in a way that manages and leverages the diversity of collectives and machine-based computation. Here we explore the role of models in helping to constitute particular collectives and how models help shape the response of the collective. It appears that models are a potentially critical resource in collecting, sharing and acting on data gathered from the operation of CASs. This points to the potential role for models in the design of HDA-CASs. In particular we are interested in how models provide a sense of identity for a collective and can provide resources that shape the potential for collective action.

Citation: Stuart Anderson, Mark Hartswood and Marina Jirotka (2014). Reflection, collectives and adaptation: the role of models in the design of Collective Adaptive Systems. In the 2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops (SASOW 2014).

Download: http://bit.ly/2jmQMN8

Abstract: This paper considers the problem of providing advice to an autonomous agent when neither the behavioural policy nor the goals of that agent are known to the advisor. We present an approach based on building a model of “commonsense” behaviour in the domain, from an aggregation of different users performing various tasks, modeled as MDPs, in the same domain. From this model, we estimate the normalcy of the trajectory given by a new agent in the domain, and provide behavioural advice based on an approximation of the trade-off in utility between potential benefits to the exploring agent and the costs incurred in giving this advice. This model is evaluated on a maze world domain by providing advice to different typesof agents, and we show that this leads to a considerable and unanimous improvement in the completion rate of their tasks.

Citation: B. Rosman, S. Ramamoorthy (2014). Giving advice to agents with hidden goals. In Proc. IEEE International Conference on Robotics and Automation (ICRA), 2014.

Download: http://bit.ly/2iKvWqc

Abstract: Given the potent and pervasive nature of modern technologies, this paper lays out the complexities involved in achieving responsible design. In order to do this we will first compare an emerging policy-oriented programme of research known as RRI (Responsible Research and Innovation) with initiatives in HCI. A focus on the similarities and differences may highlight to what extent responsibility is already and successfully embedded within the concerns and practices of design and use, and what may yet need to be incorporated for responsible design. The paper then discusses the challenges of ‘naturalising’ the very ambitious programme of RRI within specific design activities and concerns, through the lens of four analytic concepts: reflexivity; responsiveness; inclusion; and anticipation. Finally, we make a case for a pragmatic, ‘unromantic’, but engaged reinterpretation of RRI for HCI.

Citation: Grimpe, B., Hartswood, M., and Jirotka, M. (2014). Towards a closer a dialogue between Policy and Practice: Responsible Design in HCI. In Proceedings of the 2014 ACM annual conference on Human Factors in Computing Systems (CHI ’14), Toronto.

Download: http://bit.ly/2jaSWSE

Abstract: This chapter is concerned with how social order is established within collectives and the ethical problems that arise when we attempt to create and direct collectives towards particular ends. It draws on our work to establish governance principles for Smart Society—an EU project aiming to engineer Collective Adaptive Systems comprised of people and machines with diverse capabilities and goals that are able to tackle societal grand challenges. We examine how social values are implicated in and transformed by Collective Adaptive Systems, and suggest approaches to multilevel governance design that are responsive to emergent capabilities and sensitive to conflicting perspectives. Finally we illustrate our approach with a worked example of a sensor-based system in a care setting.

Citation: Hartswood, M., Grimpe, B., and Jirotka, M., “Towards the ethical governance of Smart Society”, In Miorandi, D., Maltese, V., Rovatsos, M., Nijholt., A. and Stewart, J. (eds) Social collective intelligence: Combining the powers of humans and machines Springer, 2014.

Download: http://bit.ly/2ijBXZZ

Abstract: The impact of Social Collective Intelligent Systems (SCIS) on the individual right of privacy is discussed in this chapter under the light of the relevant privacy principles of the European Data Protection Legal Framework and the OECD Privacy Guidelines. This chapter analyzes the impact and limits of profiling, provenance and reputation on the right of privacy and review the legal privacy protection for profiles. From the technical perspective, we discuss opportunities and challenges for designing privacy-preserving systems for SCIS concerning collectives and decentralized systems. Furthermore, we present a selection of privacy-enhancing technologies that are relevant for SCIS including anonymous credentials, transparency-enhancing tools and the PrimeLife Policy Language (PPL) and discuss how these technologies can help to enforce the main legal principles of the European Data Protection Legal Framework.

Citation: Fischer-Hübner, S. and Martucci, L. A., “Privacy in Social Collective Intelligence Systems”, in Miorandi, D., Maltese, V., Rovatsos, M., Nijholt., A. and Stewart, J. (eds) Social collective intelligence: Combining the powers of humans and machines Springer, 2014.

Download: http://bit.ly/2iGuZz7

A preliminary of this work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

This work was the winner of the “Best Student Paper Award” at the Seventh International Conference on Educational Data Mining (EDM 2014).

Abstract: The growing prevalence of e-learning systems and on-line courses has made educational material widely accessible to students of varying abilities, backgrounds and styles. There is thus a growing need to accommodate for individual differences in such e-learning systems. This paper presents a new algorithm for personalizing educational content to students that combines collaborative filtering algorithms with social choice theory. The algorithm constructs a “difficulty” ranking over questions for a target student by aggregating the ranking of similar students, as measured by different aspects of their performance on common past questions, such as grades, number of retries, and time spent solving questions. It infers a difficulty ranking directly over the questions for a target student, rather than ordering them according to predicted performance, which is prone to error. The algorithm was tested on two large real world data sets containing tens of thousands of students and a million records. Its performance was compared to a variety of personalization methods as well as a non-personalized method that relied on a domain expert. It was able to significantly outperform all of these approaches according to standard information retrieval metrics. Our approach can potentially be used to support teachers in tailoring problem sets and exams to individual students and students in informing them about areas they may need to strengthen..

Citation: EduRank: A Collaborative Filtering Approach to Personalization in E-learning Avi Segal, Ziv Katzir, Ya’akov Gal, Guy Shani and Bracha Shapira. EduRank: A Collaborative Filtering Approach to Personalization in E-learning. Seventh International Conference on Educational Data Mining (EDM 2014), London, England, July 2014.

Download: http://bit.ly/1WzaWlY

This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: Interaction between a user and a product like a home-appliance is sometimes a mutual relationship. A product not only provides service to a user, but also requires maintenance by the user to keep it working smoothly. If the user stops paying attention to maintenance, the product will no longer be used. To keep a sustainable relationship between a user and a product, the author proposes making a product an agent with anthropomorphic representation and interaction supported by the Anti-max Prisoner’s Dilemma game.

Keywords: Human-agent interaction, human interface, genetic programming.

Citation: Hirotaka Osawa. Sustainable Relationship with Product by Implementing Intentional Interaction.

Download: http://bit.ly/1Snueep

This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: The multidisciplinary challenge of modelling agents have been driven by theory explaining social phenomena. Yet, these generic models lack of expressiveness. For that reason, data-driven approaches to the design of agents have been pursued, mainly for modelling non-verbal behaviour. In this paper we argue that real data is not only useful for that modality, but it can also assist agent’s design in different phases of the process at different levels of granularity. Furthermore, deep data, which inform us about user’s perception, emotions and motivations is valuable to build fluid interactions with virtual humans. We illustrate our stance with two case studies where we study interpersonal conflict. One study describes the design of agents to populate a serious game aimed at teaching conflict resolution skills to children and the other describes an experiment designed to extract deep data from a dyadic interaction prone to conflict emergence.

Keywords: Virtual Agents, Design, Interpersonal Conflict, Data-driven.

Citation: Joana Campos and Ana Paiva. Interactive Social Agents from Deep Data.

Download: http://bit.ly/1STrWhr

This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: To date, a variety of automated negotiation agents have been created. While each of these agents has been shown to be effective in negotiating with people in specific environments, they lack natural language processing support required to enable real-world types of interactions. In this paper we present NegoChat, the first negotiation agent that successfully addresses this limitation. NegoChat contains several significant research contributions. First, we found that simply modifying existing agents to include an NLP module is insufficient to create these agents. Instead, the agents’ strategies must be modified to address partial agreements and issue-by-issue interactions. Second, we present NegoChat’s negotiation algorithm. This algorithm is based on bounded rationality, and specifically Aspiration Adaptation Theory (AAT). As per AAT, issues are addressed based on people’s typical urgency, or order of importance. If an agreement cannot be reached based on the value the human partner demands, the agent retreats, or downwardly lowers the value of previously agreed upon issues so that a “good enough” agreement can be reached on all issues. This incremental approach is fundamentally different from all other negotiation agents, including the state-of-the-art KBAgent. Finally, we present a rigorous evaluation of NegoChat, showing its effectiveness.

Keywords: Human-Agent Systems, Negotiation, Chat Agent.

Citation: Avi Rosenfeld. NegoChat: A Chat-Based Negotiation Agent.

Download: http://bit.ly/1XD4IQy

This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: Recently, many algorithms have been developed for autonomous agents to manage home energy use on behalf of their human owners. By so doing, it is expected that agents will be more efficient at, for example, choosing the best energy tariff to switch to when dynamically priced tariffs come about. However, to date, there has been no validation of such technologies in any field trial. In particular, it has not been shown whether users prefer fully autonomous agents as opposed to controlling their preferences manually. Hence, in this paper we describe a novel platform, called TariffAgent, to study notions of flexible autonomy in the context of tariff switching. TariffAgent uses real-world datasets and real-time electricity monitoring to instantiate a scenario where human participants may have to make, or delegate to their agent (in different ways), tariff switching decisions given uncertainties about their own consumption and tariff prices. We carried out a field trial with 10 participants and, from both quantitative and qualitative results, formulate novel design guidelines for systems that implement flexible autonomy.

Keywords: Human-Agent Interaction, Autonomous Agents, Flexible Autonomy, Energy, Smart Grid.

Citation: Alper Alan, Enrico Costanza, Joel Fisher, Sarvapali Ramchurn, Tom Rodden and Nicholas Jennings. A Field Study of Human-Agent Interaction for Electricity Tariff Switching.

Download: http://bit.ly/1MBoStF

This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: This paper proposes the Multi-Operation Patrol Scheduling System (MOPSS), a new system to generate patrols for transit system. MOPSS is based on five contributions. First, MOPSS is the first system to use three fundamentally different adversary models for the threats of fare evasion, terrorism and crime, generating three significantly different types of patrol schedule. Second, to handle uncertain interruptions in the execution of patrol schedules, MOPSS uses Markov decision processes (MDPs) in its scheduling. Third, MOPSS is the first system to account for joint activities between multiple resources, by employing the well known SMART security game model that tackles coordination between defender’s resources. Fourth, we are also the first to deploy a new Opportunistic Security Game model, where the adversary, a criminal, makes opportunistic decisions on when and where to commit crimes. Our fifth, and most important, contribution is the evaluation of MOPSS via real-world deployments, providing data from security games in the field.

Keywords: Security, Game-theory, Real-world deployment.

Citation: Francesco Delle Fave, Matthew Brown, Chao Zhang, Eric Shieh, Albert Jiang and Milind Tambe. Security Games in the Field: Deployments on a Transit System.

Download: http://bit.ly/1TcVx85

This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: This paper studies commitment strategies in three-player negotiation settings comprising human players and computer agents. We defined a new game called the Contract Game which is analogous to real-world market settings in which participants need to reach agreement over contracts in order to succeed. The game comprises three players, two service providers and one customer. The service providers compete to make repeated contract offers to the customer consisting of resource exchanges in the game. We formally analyzed the game and defined sub-game perfect equilibrium strategies for the customer and service providers that involve commitments. We conducted extensive empirical studies of these strategies in three different countries, the U.S., Israel and China. We ran several configurations in which two human participants played a single agent using the equilibrium strategies in various role configurations in the game (both customer and service providers). Our results showed that the computer agent using equilibrium strategies for the customer role was able to outperform people playing the same role in all three countries. In contrast, the computer agent playing the role of the service provider was not able to outperform people. Analysis reveals this difference in performance is due to the contracts proposed in equilibrium being significantly beneficial to the customer players, as well as irrational behavior taken by human customer players in the game.

Citation: Galit Haim, Kobi Gal, Bo An and Sarit Kraus. Equilibrium Strategies for Human-Computer Negotiation in 3-player market settings.

Download: http://bit.ly/1QfXcFa

This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: This paper deals with platforms that provide agents easier access to the type of opportunities in which they are interested (e.g., eCommerce platforms, used cars bulletins and dating web-sites). We show that under various common service schemes, a platform can benefit from not necessarily listing all the opportunities with which it is familiar, even if there is no marginal cost for listing any additional opportunity. The main implication of this result is that platforms should extract their expected-profit-maximizing service terms not based solely on the fees charged from users, but they should also use the subset that will be listed as the decision variable in the optimization problem. The analysis applies to four well-known service schemes that a platform may use to price its services. We show that neither of these schemes generally dominates the others or is dominated by any of the others. For the common case of homogeneous preferences, however, several dominance relationships can be proved, enabling the platform to identify the schemes that should be used as a default. Furthermore, the analysis provides a game-theoretic search-based explanation for a possible preference of buyers to pay for the service rather than receive it for free (e.g., when the service is sponsored by ads), a phenomena that has been justified in prior literature typically with the argument of willingness to pay a premium for an ad-free experience or more reliable platforms. The paper shows that this preference can hold both for the users and the platform in a given setting, even if both sides are fully strategic.

Keywords: Platforms and Services, Economics of Information, Two-Sided Markets, Price of Free, Service Schemes.

Citation: Chen Hajaj and David Sarne. Strategic Information Platforms – Selective Disclosure and The Price of “Free”.

Download: http://bit.ly/1VwVZSz

This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: Peer Designed Agent (PDA), computer agents developed by non-experts, is an emerging technology, widely advocated in recent literature for the purpose of replacing people in simulations and investigating human behavior. Its main premise is that the strategy programmed into these agents reliably reflect, to some extent, the behavior used by the programmer in real life. In this paper we show that PDA development has an important side effect that has not been addressed to date — the process, that merely attempts to capture one’s strategy, is also likely to affect the developer’s strategy. The phenomenon is demonstrated experimentally via the penetration detection game, using different setting variations. This result has many implications concerning the appropriate design of PDA-based simulations, and the validness of using PDAs for studying individual decision making.

Keywords: PDAs, decision making, simulation design.

Citation: Avshalom Elmalech, David Sarne and Noa Agmon. Peer Designed Agents: Just reflect or also affect?.

Download: http://bit.ly/1NvNHlq

This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: Choice selection processes are a family of bilateral games of incomplete information in which a computer agent generates advice for a human user while considering the effect of the advice on the user’s behavior in future interactions. The human and the agent may share certain goals, but are essentially self-interested. This paper extends selection processes to settings in which the actions available to the human are ordered and thus the user may be influenced by the advice even though he doesn’t necessarily follow it exactly. In this work we also consider the case in which the user obtains some observation on the sate of the world. We propose several approaches to model human decision making in such settings. We incorporate these models into two optimization techniques for the agent advice provision strategy. In the first one the agent used a social utility approach which considered the benefits and costs for both agent and person when making suggestions. In the second approach we simplified the human model in order to allow modeling and solving the agent strategy as an MDP. In an empirical evaluation involving human users on AMT, we showed that the social utility approach significantly outperformed the MDP approach.

Keywords: Human modeling, advice provision, persuasion.

Citation: Amos Azaria, Sarit Kraus, Claudia Goldman and Kobi Gal. Advice Provision for Choice Selection Processes with Ranked Options.

Download: http://bit.ly/1U002VV

Download: http://bit.ly/1XCYTme

The Smart City Expo World Congress is the international event on smart cities, bringing together over 400 cities around the world, more than 200 companies, 400 speakers and the leading institutions and experts in urban transformation. You can find more details on the event here, and watch a video of the presentation here, or below:

Our paper “Recognizing Hospital Care Activities with a Pocket Worn Smartphone” received the Best Paper Award at the 6th International Conference on Mobile Computing, Applications and Services (MobiCASE 2014).

This has been a joint effort of the German Research Centre for Artificial Intelligence and the University of Trento, and concerns the problem of “semantic gap” between machine and human semantics.

Abstract: In this work, we show how a smart-phone worn unobtrusively in a nurses coat pocket can be used to document the patient care activities performed during a regular morning routine. The main contribution is to show how, taking into account certain domain specific boundary conditions, a single sensor node worn in such an (from the sensing point of view) unfavorable location can still recognize complex, sometimes subtle activities. We evaluate our approach in a large real life dataset from day to day hospital operation. In total, 4 runs of patient care per day were collected for 14 days at a geriatric ward and annotated in high detail by following the performing nurses for the entire duration. This amounts to over 800 hours of sensor data including acceleration, gyroscope, compass, wifi and sound annotated with groundtruth at less than 1min resolution.

Index Terms: Activity Recognition, health care documentation, real-world study

Citation: Gernot Bahle, Agnes Gruenerbl, Enrico Bignotti, Mattia Zeni, Fausto Giunchiglia and Paul Lukowicz (2014): “Recognizing Hospital Care Activities with a Pocket Worn Smartphone”, 6th International Conference on Mobile Computing, Applications and Services (MobiCASE 2014, http://mobicase.org/2014/show/home)

You can find the complete list of proceedings here: http://proceedings.dev.icstweb.eu/2014/mobicase2014/file-storage/index.html#submissions

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In this issue of FoCAS Newsletter, you can read about Lucia Pannese‘s hands-on report from the 2014 FoCAS Summer School, as well as other exciting Smart Society news.

Original post here.

Summer 2014

Abstract. Advances in human computation bring the feasibility of utilizing human capabilities as services. On the other hand, we have witnessed emerging collective adaptive systems which are formed from heterogeneous types of compute units to solve complex problems. The recently introduced Social Compute Units (SCUs) present one type of these systems, which have human-based services as their core fundamental compute units. While, there is related work on forming SCUs and optimizing their performance with adaptation techniques, most of it is focused on static structures of SCUs. To provide better runtime performance and exibility management for SCUs, we present an elasticity model for SCUs and mechanisms for their elastic management which allow for certain uctuations in size, structure, performance and quality. We model states of elastic SCUs, present APIs for managing SCUs as well as metrics for controlling their elasticity with which it is possible to tailor their performance parameters at runtime within the customer-set constraints. We illustrate our contribution with an example algorithm.

Keywords: social compute units, elasticity, adaptation, collective adaptive systems

doi: http://link.springer.com/chapter/10.1007%2F978-3-319-07881-6_25

Citation: Mirela Riveni, Hong-Linh Truong, Schahram Dustdar. On the Elasticity of Social Compute Units, Springer-Verlag, 26th International Conference on Advanced Information Systems Engineering (CAiSE 2014), 16-20 June 2014, Thessaloniki, Greece. Accepted.

Download: http://bit.ly/268Pw3j

SmartSociety is proud to have co-organised this event!

Important Dates

Submission deadline: February 10th, 2014
Notification of acceptance: March 3, 2014
Workshop takes place: May 6th, 2014

The 6th International Conference on Social Informatics (SocInfo 2014) will be held in Barcelona, Spain, from November 10th to November 13th. SocInfo is an interdisciplinary venue for researchers from Computer Science, Informatics, Social Sciences and Management Sciences to share ideas and opinions, and present original research work on studying the interplay between socially-centric platforms and social phenomena. The ultimate goal of Social Informatics is to create better understanding of socially-centric platforms not just as a technology, but also as a set of social phenomena. To that end, they are inviting interdisciplinary papers, on applying information technology in the study of social phenomena, on applying social concepts in the design of information systems, on applying methods from the social sciences in the study of social computing and information systems, on applying computational algorithms to facilitate the study of social systems and human social dynamics, and on designing information and communication technologies that consider social context.

This year’s special purpose of the conference is to to bridge the gap between the social sciences and computer science. SocInfo aspires to a conference that is equally attractive to computer scientists and social scientists by putting emphasis on the methodology needed in the field of computational social science to reach long-term research objectives.

The event will also offer tutorials, workshops and keynote talks that will be tailored to address the collaboration between the two research cultures in an era when social interactions are ubiquitous and span offline, online and augmented reality worlds.

Visit their official site for information on the Calls for Papers and Workshops, research areas and more.

Important dates

Full paper submission: August 8, 2014 (23:59 Hawaii Standard Time)
Notification of acceptance: October 3, 2014
Submission of final version: October 10, 2014
Conference dates: November 10-13, 2014

Citation: Miorandi, D., Maltese, V., Rovatsos, M., Nijholt, A., Stewart, J., Social Collective Intelligence: Combining the Powers of Humans and Machines to Build a Smarter Society, Springer, 2014.

Url: http://www.springer.com/gb/book/9783319086804

Download Issue Two of the FoCAS Newsletter (PDF)

Original post here.

Winter 2014

Smart Society’s M. Rovatsos has won second prize for best challenge and vision paper in AAMAS 2014!

Abstract: This paper proposes social computation, i.e. large-scale man-machine collaboration mediated by digital interaction media, as a vision for future intelligent systems, and as a new challenge for multiagent systems research. We claim that the study of social computation suggests a re-interpretation of many traditional AI endeavours, has huge potential application benefits, and presents the field of multiagent systems with novel, exciting research questions. We introduce an abstract model of social computation that helps capture some of its core research problems more precisely. We explore the potential contribution of multiagent systems technologies to the solution of these problems by exposing the close relationship between social computation and existing methods in multiagent systems. We describe how these methods could be reused in this novel application context, what methodological implications this has, and argue that the resulting cross-fertilisation will be highly beneficial for both sides.

Keywords: social computation, human-based computation, crowdsourcing, collective intelligence.

doi: http://dl.acm.org/citation.cfm?id=2617388.2617432

Citation: M. Rovatsos. Multiagent Systems for Social Computation (challenge paper), Thirteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014), May 5-9, 2014.

Download: http://bit.ly/1W9uFYU

FoCAS has announced a summer school taking place on Crete, Greece between Monday June 23 and Friday June 27, 2014:

http://focas.eu/summer-school-2014/

Details are to be announced soon.

Important Dates

Submissions due: February 7, 2014
Notification of Acceptance: February 28, 2014 Upload of Final
Publication Files: March 10, 2014

Aim and Scope

Contemporary collaboration settings are often associated with huge, ever-increasing amounts of multiple types of data, which may vary in terms of relevance, subjectivity and importance, ranging from individual opinions to broadly accepted practices. In such settings, collective sense making is crucial for well-informed decision making. This sense making process may both utilize and provide input to intelligent information analysis tools.

This session aims to bring together researchers and practitioners from different scientific fields and research communities to exchange experiences and discuss the topic of how data-intensive and cognitively-complex sense making and decision making within diverse types of teams can be facilitated and augmented. The session will offer a venue for targeted discussion on the development and evaluation of innovative services that shift in focus from the mere collection and representation of large-scale information to its meaningful assessment, aggregation and utilization. Of particular interest are approaches that bring together the reasoning capabilities of the machine and the humans in contemporary collaborative settings.

In parallel, much interest is given to larger issues surrounding analytical practices and data sharing practices in the above settings.

Submissions are expected to cover a number of main themes (research issues), including:

• Innovative approaches to the exploration, delivery and visualization of the pertinent information.
• Novel collaboration tools and platforms for handling ill-defined domains.
• Collaborative sense making of real-world multi-faceted data.
• Novel mechanisms for understanding collaborative patterns and
  intelligent probing.
• Advances in cloud computing and scalable high-performance data
  mining for data-intensive collaboration.

Co-chairs:
Nikos Karacapilidis, University of Patras & CTI, Greece Lydia Lau,
University of Leeds, UK Pavlos Peppas, University of Patras, Greece

Submissions:
See: http://idt-14.kesinternational.org/submission.php

Contact:
Nikos Karacapilidis
University of Patras & CTI
GR 26500 Rion-Patras, Greece
Tel: (+30)-2610-997906
nikos@mech.upatras.gr
http://www.mech.upatras.gr/~nikos/