Adaptive Coalition Structure Generation in Cooperative Multi-agent Systems

In multiagent systems a coalition structure is a col- lection of pair-wise disjoint subsets of agents whose union yields the entire population. Given a characteristic funct ion quantifying the worth of agent subsets, searching for optimal coalition structures (i.e. where the sum of subsets' worth i s maximal) is a well-known NP-hard combinatorial optimiza- tion problem. While existing algorithms (either deterministic or stochastic) deal with time-invariant goal functions, th e fo- cus here is on dynamic settings, where the worth of agent sub- sets possibly varies over time in an unknown and unpredictable fashion. The aim is to design an adaptive dynamic process gen- erating coalition structures with high worth most of the times. To this end, detecting variations in the worth of agent sub- sets becomes crucial. The proposed method takes into account such (possible) changes by intensifying the exploration activity whenever they are detected. The performance with respect to the worth of optimal coalition structures is evaluated thro ugh simulations.