Intelligent Autonomous Systems

Intelligent Autonomous Systems

Antifragility for Intelligent Autonomous Systems

Antifragile systems grow measurably better in the presence of hazards. This is in contrast to fragile systems which break down in the presence of hazards, robust systems that tolerate hazards up to a certain degree, and resilient systems that – like selfhealing systems – revert to their earlier expected behavior after a period of convalescence. The notion of antifragility was introduced by Tale...

Learning by Collaboration in Intelligent Autonomous Systems

Very few learning systems applied to problem solving have focused on learning operator definitions from the interaction with a completely unknown environment. Autonomous Intelligent Systems (AIS) deal with that issue by means of architectures where learning is achieved by establishing plans, executing those plans in the environment, analyzing the results of the execution, and combining new evid...

Learning Life Cycle in Autonomous Intelligent Systems

Autonomous Intelligent Systems (AIS) integrate planning, learning, and execution in a closed loop, showing an autonomous intelligent behavior. A Learning Life Cycle (LLC) Operators, Trained Base Operators and World Interaction Operators. The extension of the original architecture to support the new type of operators is presented.

Learning Planning Operators in Autonomous Intelligent Systems

Considerations are accomplished on the problem of building planning operators; the limits of the problem are defined; a method of building planning operators based on the application of heuristic of generated planning operators mutation is proposed, the definition of each heuristic is given, the limits of the problem of planning operators weighting are defined, a weighting method is proposed. A...