Rule Creation and Rule Learning Through Environmental Exploration

The task of learning from environment is specified. It requires the learner to infer the laws of the environment in terms of its percepts and actions, and use the laws to solve problems. Based on research on problem space creation and discrimination learning, this paper reports an approach in which exploration, rule creation and rule learning are coordinated in a single framework. With this approach, the system LIVE creates STRIPS-Iike rules by noticing the changes in the environment when actions are taken, and later refines the rules by explaining the failures of their predictions. Unlike many other learning systems, since LIVE treats learning and problem solving as interleaved activities , no training instance nor any concept hierarchy is necessary to start learning. Furthermore , the approach is capable of discovering hidden features from the environment when normal discrimination process fails to make any progress. 1 Introduction While solving problems in a new environment, as when we learn how to swim, a learning system must explore the environment to correlate its actions with its senses, to induce the laws of the environment, and to create feasible problem representations for problem solving. We refer to this task as learning from environment, and give its specification in Table 1.