Building architectures for autonomous rational behavior requires the integration of several AI components, such as planning, learning and execution monitoring. In most cases, the ...
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
Learning Bayesian networks from data has been studied extensively in the evolutionary algorithm communities [Larranaga96, Wong99]. We have previously explored extending some of the...
Current explanation-based generalization (EBG) techniques can perform badly when the problem being solved involves recursion. Often an infinite series of learned concepts are gene...
The authors present experimental and simulation results of an outcome-based learning model as it applies to the identification of emerging threats. This model integrates judgment,...
Ignacio J. Martinez-Moyano, Stephen H. Conrad, Dav...