We present a centralized and a distributed algorithms for scheduling multi-task agents in heterogeneous networks. Our centralized algorithm has an upper bound on the overall compl...
This paper addresses agents' intentions as building blocks of imitation learning that abstract local situations of the agent, and proposes a hierarchical hidden Markov model ...
In a combinatorial auction, a set of resources is for sale, and agents can bid on subsets of these resources. In a voting setting, the agents decide among a set of alternatives by...
This paper presents a novel method for automatic evaluation of conversational agents. In the method, information about users’ attitudes and sentiments to conversational agents a...
Michal Ptaszynski, Pawel Dybala, Shinsuke Higuchi,...
This paper presents the Agent MOdeling LAnguage (AMOLA). This language provides the syntax and semantics for creating models of multi-agent systems covering the analysis and design...