Agent-Based Participatory Simulations: Merging Multi-Agent Systems and Role-Playing Games

In 2001, Olivier Barreteau proposed to jointly use multi-agent systems and role-playing games for purposes of research, training and negotiation support in the field of renewable resource management. This joint use was later labeled the "MAS/RPG methodology" and this approach is one of the foundation stones of the ComMod movement. In this article, we present an alternative method called "agent-based participatory simulations". These simulations are multi-agent systems where human participants control some of the agents. The experiments we conducted prove that it is possible to successfully merge multi-agent systems and role-playing games. We argue that agent-based participatory simulations are also a significant improvement over the MAS/RPG approach, opening new perspectives and solving some of the problems generated by the joint use of role-playing games and multi-agent systems. The advantages are at least threefold. Because all interactions are computer mediated, they can be recorded and this record can be processed and used to improve the understanding of participants and organizers alike. Because of the merge, agent-based participatory simulations decrease the distance between the agent-based model and the behavior of participants. Agent-based participatory simulations allow for computer-based improvements such as the introduction of eliciting assistant agents with learning capabilities.Agent-Based Participatory Simulations, Multi-Agent Systems, Role-Playing Games, Validation, Negotiation Support Tool

Integrative Use of Information Extraction, Semantic Matchmaking and Adaptive Coupling Techniques in Support of Distributed Information Processing and Decision-Making

In order to press maximal cognitive benefit from their social, technological and informational environments, military coalitions need to understand how best to exploit available information assets as well as how best to organize their socially-distributed information processing activities. The International Technology Alliance (ITA) program is beginning to address the challenges associated with enhanced cognition in military coalition environments by integrating a variety of research and development efforts. In particular, research in one component of the ITA ('Project 4: Shared Understanding and Information Exploitation') is seeking to develop capabilities that enable military coalitions to better exploit and distribute networked information assets in the service of collective cognitive outcomes (e.g. improved decision-making). In this paper, we provide an overview of the various research activities in Project 4. We also show how these research activities complement one another in terms of supporting coalition-based collective cognition

Efficient computation of the Shapley value for game-theoretic network centrality

The Shapley value—probably the most important normative payoff division scheme in coalitional games—has recently been advocated as a useful measure of centrality in networks. However, although this approach has a variety of real-world applications (including social and organisational networks, biological networks and communication networks), its computational properties have not been widely studied. To date, the only practicable approach to compute Shapley value-based centrality has been via Monte Carlo simulations which are computationally expensive and not guaranteed to give an exact answer. Against this background, this paper presents the first study of the computational aspects of the Shapley value for network centralities. Specifically, we develop exact analytical formulae for Shapley value-based centrality in both weighted and unweighted networks and develop efficient (polynomial time) and exact algorithms based on them. We empirically evaluate these algorithms on two real-life examples (an infrastructure network representing the topology of the Western States Power Grid and a collaboration network from the field of astrophysics) and demonstrate that they deliver significant speedups over the Monte Carlo approach. Fo

What's in it for me? Recommendation of Peers in Networked Innovation

Sie R. L. L., Bitter-Rijpkema, M., & Sloep, P. B. (2011). What's in it for me? Recommendation of Peers in Networked Innovation. Journal of Universal Computer Science, 17(12), 1659-1672.Several studies have shown that connecting to people in other networks foster creativity and innovation. However, it is often difficult to tell what the prospective value of such alliances is. Cooperative game theory offers an a priori estimation of the value of future collaborations. We present an agent-based social simulation approach to recommending valuable peers in networked innovation. Results indicate that power as such does not lead to a winning coalition in networked innovation. The recommendation proved to be successful for low-strength agents, which connected to high-strength agents in their network. Future work includes tests in real-life and other recommendation strategies.idSpac