Multiagent reinforcement learning problems are especially difficult because of their dynamism and the size of joint state space. In this paper a new benchmark problem is proposed, ...
This paper presents a multiagent architecture constructed for learning from the interaction between the atmosphere and the ocean. The ocean surface and the atmosphere exchange carb...
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 ...
Adaptivity has become a prominent research topic during the past decades. There is a variety of application areas where adaptation can add benefit to systems, reaching from shoppi...
Ubiquitous system can be considered as the intelligent space, in which many kinds of component are connected by networks and also each component recognizes their connection and coo...