Modelling Socially Intelligent Agents

The perspective of modelling agents rather than using them for a specificed purpose entails a difference in approach. In particular an emphasis on veracity as opposed to efficiency. An approach using evolving populations of mental models is described that goes some way to meet these concerns. It is then argued that social intelligence is not merely intelligence plus interaction but should allow for individual relationships to develop between agents. This means that, at least, agents must be able to distinguish, identify, model and address other agents, either individually or in groups. In other words that purely homogeneous interaction is insufficient. Two example models are described that illustrate these concerns, the second in detail where agents act and communicate socially, where this is determined by the evolution of their mental models. Finally some problems that arise in the interpretation of such simulations is discussed

Methods and Tools for the Microsimulation and Forecasting of Household Expenditure - A Review

This paper reviews potential methods and tools for the microsimulation and forecasting of household expenditure. It begins with a discussion of a range of approaches to the forecasting of household populations via agent-based modelling tools. Then it evaluates approaches to the modelling of household expenditure. A prototype implementation is described and the paper concludes with an outline of an approach to be pursued in future work

Methods and Tools for the Microsimulation and Forecasting of Household Expenditure

This paper reviews potential methods and tools for the microsimulation and forecasting of household expenditure. It begins with a discussion of a range of approaches to the forecasting of household populations via agent-based modelling tools. Then it evaluates approaches to the modelling of household expenditure. A prototype implementation is described and the paper concludes with an outline of an approach to be pursued in future work

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

Evaluating how agent methodologies support the specification of the normative environment through the development process

[EN] Due to the increase in collaborative work and the decentralization of processes in many domains, there is an expanding demand for large-scale, flexible and adaptive software systems to support the interactions of people and institutions distributed in heterogeneous environments. Commonly, these software applications should follow specific regulations meaning the actors using them are bound by rights, duties and restrictions. Since this normative environment determines the final design of the software system, it should be considered as an important issue during the design of the system. Some agent-oriented software engineering methodologies deal with the development of normative systems (systems that have a normative environment) by integrating the analysis of the normative environment of a system in the development process. This paper analyses to what extent these methodologies support the analysis and formalisation of the normative environment and highlights some open issues of the topic.This work is partially supported by the PROMETEOII/2013/019, TIN2012-36586-C03-01, FP7-29493, TIN2011-27652-C03-00, CSD2007-00022 projects, and the CASES project within the 7th European Community Framework Program under the grant agreement No 294931.Garcia Marques, ME.; Miles, S.; Luck, M.; Giret Boggino, AS. (2014). Evaluating how agent methodologies support the specification of the normative environment through the development process. Autonomous Agents and Multi-Agent Systems. 1-20. https://doi.org/10.1007/s10458-014-9275-zS120Cossentino, M., Hilaire, V., Molesini, A., & Seidita, V. (Eds.). (2014). Handbook on agent-oriented design processes (Vol. VIII, 569 p. 508 illus.). Berlin: Springer.Akbari, O. (2010). A survey of agent-oriented software engineering paradigm: Towards its industrial acceptance. Journal of Computer Engineering Research, 1, 14–28.Argente, E., Botti, V., Carrascosa, C., Giret, A., Julian, V., & Rebollo, M. (2011). An abstract architecture for virtual organizations: The THOMAS approach. Knowledge and Information Systems, 29(2), 379–403.Argente, E., Botti, V., & Julian, V. (2009). GORMAS: An organizational-oriented methodological guideline for open MAS. In Proceedings of AOSE’09 (pp. 440–449).Argente, E., Botti, V., & Julian, V. (2009). Organizational-oriented methodological guidelines for designing virtual organizations. In Distributed computing, artificial intelligence, bioinformatics, soft computing, and ambient assisted living. Lecture Notes in Computer Science (Vol. 5518, pp. 154–162).Boella, G., Pigozzi, G., & van der Torre, L. (2009). Normative systems in computer science—Ten guidelines for normative multiagent systems. In G. Boella, P. Noriega, G. Pigozzi, & H. Verhagen (Eds.), Normative multi-agent systems, number 09121 in Dagstuhl seminar proceedings.Boella, G., Torre, L., & Verhagen, H. (2006). Introduction to normative multiagent systems. Computational and Mathematical Organization Theory, 12(2–3), 71–79.Bogdanovych, A., Esteva, M., Simoff, S., Sierra, C., & Berger, H. (2008). A methodology for developing multiagent systems as 3d electronic institutions. In M. Luck & L. Padgham (Eds.), Agent-Oriented Software Engineering VIII (Vol. 4951, pp. 103–117). Lecture Notes in Computer Science. Berlin: Springer.Boissier, O., Padget, J., Dignum, V., Lindemann, G., Matson, E., Ossowski, S., Sichman, J., & Vazquez-Salceda, J. (2006). Coordination, organizations, institutions and norms in multi-agent systems. LNCS (LNAI) (Vol. 3913).Bordini, R. H., Fisher, M., Visser, W., & Wooldridge, M. (2006). Verifying multi-agent programs by model checking. In Autonomous agents and multi-agent systems (Vol. 12, pp. 239–256). Hingham, MA: Kluwer Academic Publishers.Botti, V., Garrido, A., Giret, A., & Noriega, P. (2011). The role of MAS as a decision support tool in a water-rights market. In Post-proceedings workshops AAMAS2011 (Vol. 7068, pp. 35–49). Berlin: Springer.Breaux, T. (2009). Exercising due diligence in legal requirements acquisition: A tool-supported, frame-based approach. In Proceedings of the IEEE international requirements engineering conference (pp. 225–230).Breaux, T. D., & Baumer, D. L. (2011). Legally reasonable security requirements: A 10-year ftc retrospective. Computers and Security, 30(4), 178–193.Breaux, T. D., Vail, M. W., & Anton, A. I. (2006). Towards regulatory compliance: Extracting rights and obligations to align requirements with regulations. In Proceedings of the 14th IEEE international requirements engineering conference, RE ’06 (pp. 46–55). Washington, DC: IEEE Computer Society.Bresciani, P., Perini, A., Giorgini, P., Giunchiglia, F., & Mylopoulos, J. (2004). Tropos: An agent-oriented software development methodology. Autonomous Agents and Multi-Agent Systems, 8(3), 203–236.Cardoso, H. L., & Oliveira, E. (2008). A contract model for electronic institutions. In COIN’07: Proceedings of the 2007 international conference on Coordination, organizations, institutions, and norms in agent systems III (pp. 27–40).Castor, A., Pinto, R. C., Silva, C. T. L. L., & Castro, J. (2004). Towards requirement traceability in tropos. In WER (pp. 189–200).Chopra, A., Dalpiaz, F., Giorgini, P., & Mylopoulos, J. (2009). Modeling and reasoning about service-oriented applications via goals and commitments. ICST conference on digital business.Cliffe, O., Vos, M., & Padget, J. (2006). Specifying and analysing agent-based social institutions using answer set programming. In O. Boissier, J. Padget, V. Dignum, G. Lindemann, E. Matson, S. Ossowski, J. Sichman, & J. Vázquez-Salceda (Eds.), Coordination, organizations, institutions, and norms in multi-agent systems. Lecture Notes in Computer Science (Vol. 3913, pp. 99–113). Springer. Berlin.Criado, N., Argente, E., Garrido, A., Gimeno, J. A., Igual, F., Botti, V., Noriega, P., & Giret, A. (2011). Norm enforceability in Electronic Institutions? In Coordination, organizations, institutions, and norms in agent systems VI (Vol. 6541, pp. 250–267). Springer.Dellarocas, C., & Klein, M. (2001). Contractual agent societies. In R. Conte & C. Dellarocas (Eds.), Social order in multiagent systems (Vol. 2, pp. 113–133)., Multiagent Systems, Artificial Societies, and Simulated Organizations New York: Springer.DeLoach, S. A. (2008). Developing a multiagent conference management system using the o-mase process framework. In Proceedings of the international conference on agent-oriented software engineering VIII (pp. 168–181).DeLoach, S. A., & Garcia-Ojeda, J. C. (2010). O-mase; a customisable approach to designing and building complex, adaptive multi-agent systems. International Journal of Agent-Oriented Software Engineering, 4(3), 244–280.DeLoach, S. A., Padgham, L., Perini, A., Susi, A., & Thangarajah, J. (2009). Using three aose toolkits to develop a sample design. International Journal Agent-Oriented Software Engineering, 3, 416–476.Dignum, F., Dignum, V., Thangarajah, J., Padgham, L., & Winikoff, M. (2007). Open agent systems? Eighth international workshop on agent oriented software engineering (AOSE) in AAMAS07.Dignum, V. (2003). A model for organizational interaction:based on agents, founded in logic. PhD thesis, Utrecht University.Dignum, V., Meyer, J., Dignum, F., & Weigand, H. (2003). Formal specification of interaction in agent societies. Formal approaches to agent-based systems (Vol. 2699).Dignum, V., Vazquez-Salceda, J., & Dignum, F. (2005). Omni: Introducing social structure, norms and ontologies into agent organizations. In R. Bordini, M. Dastani, J. Dix, & A. Seghrouchni (Eds.)Programming multi-agent systems. Lecture Notes in Computer Science (Vol. 3346, pp. 181–198). Berlin: Springer.d’Inverno, M., Luck, M., Noriega, P., Rodriguez-Aguilar, J., & Sierra, C. (2012). Communicating open systems, 186, 38–94.Elsenbroich, C., & Gilbert, N. (2014). Agent-based modelling. In Modelling norms (pp. 65–84). Dordrecht: Springer.Esteva, M., Rosell, B., Rodriguez, J. A., & Arcos, J. L. (2004). AMELI: An agent-based middleware for electronic institutions. In AAMAS04 (pp. 236–243).Fenech, S., Pace, G. J., & Schneider, G. (2009). Automatic conflict detection on contracts. In Proceedings of the 6th international colloquium on theoretical aspects of computing, ICTAC ’09 (pp. 200–214).Garbay, C., Badeig, F., & Caelen, J. (2012). Normative multi-agent approach to support collaborative work in distributed tangible environments. In Proceedings of the ACM 2012 conference on computer supported cooperative work companion, CSCW ’12 (pp. 83–86). New York, NY: ACM.Garcia, E., Giret, A., & Botti, V. (2011). Regulated open multi-agent systems based on contracts. In Information Systems Development (pp. 243–255).Garcia, E., Tyson, G., Miles, S., Luck, M., Taweel, A., Staa, T. V., & Delaney, B. (2012). An analysis of agent-oriented engineering of e-health systems. In 13th international eorkshop on sgent-oriented software engineering (AOSE-AAMAS).Garcia, E., Tyson, G., Miles, S., Luck, M., Taweel, A., Staa, T. V., and Delaney, B. (2013). Analysing the Suitability of Multiagent Methodologies for e-Health Systems. In Agent-Oriented Software Engineering XIII, volume 7852, pages 134–150. Springer-Verlag.Garrido, A., Giret, A., Botti, V., & Noriega, P. (2013). mWater, a case study for modeling virtual markets. In New perspectives on agreement technologies (Vol. Law, Gover, pp. 563–579). Springer.Gteau, B., Boissier, O., & Khadraoui, D. (2006). Multi-agent-based support for electronic contracting in virtual enterprises. IFAC Symposium on Information Control Problems in Manufacturing (INCOM), 150(3), 73–91.Hollander, C. D., & Wu, A. S. (2011). The current state of normative agent-based systems. Journal of Artificial Societies and Social Simulation, 14(2), 6.Hsieh, F.-S. (2005). Automated negotiation based on contract net and petri net. In E-commerce and web technologies. Lecture Notes in Computer Science (Vol. 3590, pp. 148–157).Kollingbaum, M., Jureta, I. J., Vasconcelos, W., & Sycara, K. (2008). Automated requirements-driven definition of norms for the regulation of behavior in multi-agent systems. In Proceedings of the AISB 2008 workshop on behaviour regulation in multi-agent systems, Aberdeen, Scotland, U.K., April 2008.Li, T., Balke, T., Vos, M., Satoh, K., & Padget, J. (2013). Detecting conflicts in legal systems. In Y. Motomura, A. Butler, & D. Bekki (Eds.), New Frontiers in Artificial Intelligence (Vol. 7856, pp. 174–189)., Lecture Notes in Computer Science Berlin Heidelberg: Springer.Lomuscio, A., Qu, H., & Solanki, M. (2010) Towards verifying contract regulated service composition. Journal of Autonomous Agents and Multi-Agent Systems (pp. 1–29).Lopez, F., Luck, M., & d’Inverno, M. (2006). A normative framework for agent-based systems. Computational and Mathematical Organization Theory, 12, 227–250.Lpez, F. y, Luck, M., & dInverno, M. (2006). A normative framework for agent-based systems. Computational and Mathematical Organization Theory, 12(2–3), 227–250.Mader, P., & Egyed, A. (2012). Assessing the effect of requirements traceability for software maintenance. In 28th IEEE International Conference on Software Maintenance (ICSM) (pp. 171–180), Sept 2012.Mao, X., & Yu, E. (2005). Organizational and social concepts in agent oriented software engineering. In AOSE IV. Lecture Notes in Artificial Intelligence (Vol. 3382, pp. 184–202).Meyer, J.-J. C., & Wieringa, R. J. (Eds.). (1993). Deontic logic in computer science: Normative system specification. Chichester, UK: Wiley.Okouya, D., & Dignum, V. (2008). Operetta: A prototype tool for the design, analysis and development of multi-agent organizations (demo paper). In AAMAS (pp. 1667–1678).Malone, T. W., Smith J. B., & Olson, G. M. (2001). Coordination theory and collaboration technology. Mahwah, NJ: Lawrence Erlbaum Associates.Oren, N., Panagiotidi, S., Vázquez-Salceda, J., Modgil, S., Luck, M., & Miles, S. (2009). Towards a formalisation of electronic contracting environments. COIN (pp. 156–171).Osman, N., Robertson, D., & Walton, C. (2006). Run-time model checking of interaction and deontic models for multi-agent systems. In AAMAS ’06: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (pp. 238–240). 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A Common Protocol for Agent-Based Social Simulation

Traditional (i.e. analytical) modelling practices in the social sciences rely on a very well established, although implicit, methodological protocol, both with respect to the way models are presented and to the kinds of analysis that are performed. Unfortunately, computer-simulated models often lack such a reference to an accepted methodological standard. This is one of the main reasons for the scepticism among mainstream social scientists that results in low acceptance of papers with agent-based methodology in the top journals. We identify some methodological pitfalls that, according to us, are common in papers employing agent-based simulations, and propose appropriate solutions. We discuss each issue with reference to a general characterization of dynamic micro models, which encompasses both analytical and simulation models. In the way, we also clarify some confusing terminology. We then propose a three-stage process that could lead to the establishment of methodological standards in social and economic simulations.Agent-Based, Simulations, Methodology, Calibration, Validation, Sensitivity Analysis

An interactive, generative Punch and Judy show using institutions, ASP and emotional agents

Using Punch and Judy as a story domain, we describe an interactive puppet show, where the flow and content of the story can be influenced by the actions of the audience. As the puppet show is acted out, the audience reacts to events by cheering or booing the characters. This affects the agents’ emotional state, potentially causing them to change their actions, altering the course of the narrative. An institutional normative model is used to constrain the narrative so that it remains consistent with the Punch and Judy canon. Through this vignette of a socio-technical system (STS), comprising human and software actors, an institutional model – derived from narrative theory – and (simplistic) technological interaction artifacts, we begin to be able to explore some of the issues that can arise in STS through the prism of the World-Institution-Technology (WIT) model

Automatic Music Composition using Answer Set Programming

Music composition used to be a pen and paper activity. These these days music is often composed with the aid of computer software, even to the point where the computer compose parts of the score autonomously. The composition of most styles of music is governed by rules. We show that by approaching the automation, analysis and verification of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can be easily built. This application paper describes the use of answer set programming to construct an automated system, named ANTON, that can compose melodic, harmonic and rhythmic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The combination of harmonic, rhythmic and melodic composition in a single framework makes ANTON unique in the growing area of algorithmic composition. With near real-time composition, ANTON reaches the point where it can not only be used as a component in an interactive composition tool but also has the potential for live performances and concerts or automatically generated background music in a variety of applications. With the use of a fully declarative language and an "off-the-shelf" reasoning engine, ANTON provides the human composer a tool which is significantly simpler, more compact and more versatile than other existing systems. This paper has been accepted for publication in Theory and Practice of Logic Programming (TPLP).Comment: 31 pages, 10 figures. Extended version of our ICLP2008 paper. Formatted following TPLP guideline

A Common Protocol for Agent-Based Social Simulation

Traditional (i.e. analytical) modelling practices in the social sciences rely on a very well established, although implicit, methodological protocol, both with respect to the way models are presented and to the kinds of analysis that are performed. Unfortunately, computer-simulated models often lack such a reference to an accepted methodological standard. This is one of the main reasons for the scepticism among mainstream social scientists that results in low acceptance of papers with agent-based methodology in the top journals. We identify some methodological pitfalls that, according to us, are common in papers employing agent-based simulations, and propose appropriate solutions. We discuss each issue with reference to a general characterization of dynamic micro models, which encompasses both analytical and simulation models. In the way, we also clarify some confusing terminology. We then propose a three-stage process that could lead to the establishment of methodological standards in social and economic simulations.Agent-based, simulations, methodology, calibration, validation.

A review of Multi-Agent Simulation Models in Agriculture

Multi-Agent Simulation (MAS) models are intended to capture emergent properties of complex systems that are not amenable to equilibrium analysis. They are beginning to see some use for analysing agricultural systems. The paper reports on work in progress to create a MAS for specific sectors in New Zealand agriculture. One part of the paper focuses on options for modelling land and other resources such as water, labour and capital in this model, as well as markets for exchanging resources and commodities. A second part considers options for modelling agent heterogeneity, especially risk preferences of farmers, and the impacts on decision-making. The final section outlines the MAS that the authors will be constructing over the next few years and the types of research questions that the model will help investigate.multi-agent simulation models, modelling, agent-based model, cellular automata, decision-making, Crop Production/Industries, Environmental Economics and Policy, Farm Management, Land Economics/Use, Livestock Production/Industries,