A machine learning technique for handling scenarios of interaction between conflicting agents is suggested. Scenarios are represented by directed graphs with labeled vertices (for ...
Boris Galitsky, Sergei O. Kuznetsov, Mikhail V. Sa...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
Reasoning with hypothetical cases helps decision-makers evaluate alternate hypotheses for deciding a case. The hypotheticals demonstrate the sensitivity of a hypothesis to apparen...
We analyze the main motivations that lead to the present need for supporting continuous software evolution, and discuss some of the reasons for change requirements. Achieving softw...
This paper proposes a two-phase example-based machine translation methodology which develops translation templates from examples and then translates using template matching. This ...