Chattrakul Sombattheera

A pruning-based algorithm for computing optimal coalition structures in linear production domains

Computing optimal coalition structures is an important research problem in multi-agent systems. It has rich application in real world problems, including logistics and supply chains. We study computing optimal coalition structures in linear production domains. The common goal of the agents is to maximize the systems profit. Agents perform two steps: i) deliberate profitable coalitions, and ii) exchange computed coalitions and generate coalition structures. In our previous studies, agents keep growing their coalitions from the singleton ones in the deliberation step. This work takes opposite approach that agents keep pruning unlikely profitable coalitions from the grand coalition. It also relaxes the strict condition of coalition center, which yields the minimal cost to the coalition. Here, agents merely keep generating profitable coalitions. Furthermore, we introduce new concepts, i.e., best coalitions and pattern, in our algorithm and provide an example of how it can work. Lastly, we show that our algorithm outperforms exhaustive search in generating optimal coalition structures in terms of elapsed time and number of coalition structures generated.

Agent-based prototyping of web-based systems

Agent-oriented conceptual modelling in notations such as the i* framework [13] have gained considerable currency in the recent past. Such notations model organizational context and offer high-level social/ anthropo-morphic abstractions (such as goals, tasks, softgoals and dependencies) as modelling constructs. It has been argued that such notations help answer questions such as what goals exist, how key actors depend on each other and what alternatives must be considered. Our contribution in this paper is to show an approach to executing high-level requirements models represented in the i* agent-oriented conceptual modelling language. We achieve this by translating these models into sets of interacting agents implemented in the 3APL language. This approach enables us to analyze early phase system models by performing rule-/consistency-checking at higher-levels of abstraction. We show how this approach finds special application in the analysis of high-level models of a web-based system.

A distributed branch-and-bound algorithm for computing optimal coalition structures

Coalition formation is an important area of research in multi-agent systems. Computing optimal coalition structures for a large number of agents is an important problem in coalition formation but has received little attention in the literature. Previous studies assume that each coalition value is known a priori. This assumption is impractical in real world settings. Furthermore, the problem of finding coalition values become intractable for even a relatively small number of agents. This work proposes a distributed branch-and-bound algorithm for computing optimal coalition structures in linear production domain, where each coalition value is not known a priori. The common goal of the agents is to maximize the systems profit. In our algorithm, agents perform two tasks: i) deliberate profitable coalitions, and ii) cooperatively compute optimal coalition structures. We show that our algorithm outperforms exhaustive search in generating optimal coalition structure in terms of elapses time and number of coalition structures generated.

Supporting dynamic supply networks with agent-based coalitions

This work extends our previous work to offer richer support for collaboration across supply networks. The role of agents are divided into three sectors at any point in time: buyers, sellers and LPs. Agents take two steps to form coalitions: i) agents in each sector sequencially form primary coalitions in order to increase bargaining power, selling capacity or service efficiency, and ii) agents form secondary coalitions across sectors in order to finalize the deal and deliver goods to buyers. We propose a negotiation protocol and deliberation mechanism. The negotiation protocol allows thorough communication among agents within and across sectors. The deliberation mechanism allows agents to consider potential coalition members and attractive payoffs for them. We provide examples of how they can help agents form coalitions successfully.