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

A Logic-Based Representation for Coalitional Games with Externalities

We consider the issue of representing coalitional games in multiagent systems that exhibit externalities from coalition formation, i.e., systems in which the gain from forming a coalition may be affected by the formation of other co-existing coalitions. Although externalities play a key role in many real-life situations, very little attention has been given to this issue in the multi-agent system literature, especially with regard to the computational aspects involved. To this end, we propose a new representation which, in the spirit of Ieong and Shoham [9], is based on Boolean expressions. The idea behind our representation is to construct much richer expressions that allow for capturing externalities induced upon coalitions. We show that the new representation is fully expressive, at least as concise as the conventional partition function game representation and, for many games, exponentially more concise. We evaluate the efficiency of our new representation by considering the problem of computing the Extended and Generalized Shapley value, a powerful extension of the conventional Shapley value to games with externalities. We show that by using our new representation, the Extended and Generalized Shapley value, which has not been studied in the computer science literature to date, can be computed in time linear in the size of the input

Strategy-Proof Coalition Formation

We analyze coalition formation problems in which a group of agents is partitioned into coalitions and agents' preferences only depend on the coalition they belong to. We study rules that associate to each profile of agents' preferences a partition of the society. We focus on strategy-proof rules on restricted domains of preferences, as the domains of additively representable or separable preferences. In such domains, the only strategy-proof and individually rational rules that satisfy either Pareto efficiency or non-bossiness and flexibility are single-lapping rules. Single-lapping rules are characterized by severe restrictions on the set of feasible coalitions that are consisitent with hierarchical organizations. These restrictions are necessary and sufficient for the existence of a unique core-stable partition. This fact implies that single-lapping rules always select the associated unique core-stable partition. Thus, our results highlight the relation between the non-cooperative concept of strategy-proofness and the cooperative concept of uniqueness of core-stable partitions.Coalition Formation; Strategy-Proofness; Single-Lapping Property; Core-Stability; Matching Problems.

MULTIAGENT SYSTEMS FOR SHOP FLOOR ARHITECTURE MANAGEMENT

The paper presents the problem of shop floor agility. In order to cope with the disturbances and uncertainties that characterise the current business scenarios faced by manufacturing companies, the capability of their shop floors needs to be improved quickly, such that these shop floors may be adapted, changed or become easily modifiable (shop floor reengineering). One of the critical elements in any shop floor reengineering process is the way the control/supervision architecture is changed or modified to accommodate for the new process and equipment. This paper, therefore, proposes an multi-agent architecture to support the fast adaptation or changes in the control/supervision architecture.multi-agent system, shop floor agility, control/supervision architecture, virtual organisation.

On the convergence of autonomous agent communities

This is the post-print version of the final published paper that is available from the link below. Copyright @ 2010 IOS Press and the authors.Community is a common phenomenon in natural ecosystems, human societies as well as artificial multi-agent systems such as those in web and Internet based applications. In many self-organizing systems, communities are formed evolutionarily in a decentralized way through agents' autonomous behavior. This paper systematically investigates the properties of a variety of the self-organizing agent community systems by a formal qualitative approach and a quantitative experimental approach. The qualitative formal study by applying formal specification in SLABS and Scenario Calculus has proven that mature and optimal communities always form and become stable when agents behave based on the collective knowledge of the communities, whereas community formation does not always reach maturity and optimality if agents behave solely based on individual knowledge, and the communities are not always stable even if such a formation is achieved. The quantitative experimental study by simulation has shown that the convergence time of agent communities depends on several parameters of the system in certain complicated patterns, including the number of agents, the number of community organizers, the number of knowledge categories, and the size of the knowledge in each category

Internal Hierarchy and Stable Coalition Structures

When an agent decides whether to join a coalition or not, she must consider both i) the expected strength of the coalition and ii) her position in the vertical structure within the coalition. We establish that there exists a positive relationship between the degree of inequality in remuneration across ranks within coalitions and the number of coalitions to be formed. When coalition size is unrestricted, in all stable systems the endogenous coalitions must be mixed and balanced in terms of members' abilities, with no segregation. When coalitions must have a fixed finite size, stable systems display segregation by clusters while maintaining the aforesaid feature within clusters.Stable Systems, Abilities, Hierarchy, Cyclic Partition

Contextual and Possibilistic Reasoning for Coalition Formation

In multiagent systems, agents often have to rely on other agents to reach their goals, for example when they lack a needed resource or do not have the capability to perform a required action. Agents therefore need to cooperate. Then, some of the questions raised are: Which agent(s) to cooperate with? What are the potential coalitions in which agents can achieve their goals? As the number of possibilities is potentially quite large, how to automate the process? And then, how to select the most appropriate coalition, taking into account the uncertainty in the agents' abilities to carry out certain tasks? In this article, we address the question of how to find and evaluate coalitions among agents in multiagent systems using MCS tools, while taking into consideration the uncertainty around the agents' actions. Our methodology is the following: We first compute the solution space for the formation of coalitions using a contextual reasoning approach. Second, we model agents as contexts in Multi-Context Systems (MCS), and dependence relations among agents seeking to achieve their goals, as bridge rules. Third, we systematically compute all potential coalitions using algorithms for MCS equilibria, and given a set of functional and non-functional requirements, we propose ways to select the best solutions. Finally, in order to handle the uncertainty in the agents' actions, we extend our approach with features of possibilistic reasoning. We illustrate our approach with an example from robotics

A unified approach to the revelation of public goods preferences and to optimal income taxation

We study a large economy model in which individuals have private information about their productive abilities and their preferences for public goods. A mechanism design approach is used to characterize implementable tax and expenditure policies. A robustness requirement in the sense of Bergemann and Morris (2005) yields individual incentive compatibility constraints that are equivalent to those in the theory of optimal income taxation in the tradition of Mirrlees (1971). Adding a requirement of coalition-proofness yields a set of collective incentive conditions which are akin those in the literature on public goods provision under private information on preferences, in the tradition of Clarke (1971) and Groves (1973).Optimal Taxation, Public goods provision, Revelation of Preferences, Robust Mechanism Design