Architecture and Representations

作者: Nick Hawes , Jeremy L. Wyatt , Mohan Sridharan , Henrik Jacobsson , Richard Dearden

DOI: 10.1007/978-3-642-11694-0_2

关键词: Robot architectureArchitectureHuman–computer interactionIntelligent decision support systemSystems engineeringDesign spaceSystem buildingComputer scienceBinding problemPartially observable Markov decision processSpace (commercial competition)

摘要: The study of architectures to support intelligent behaviour is certainly the broadest, and arguably one most ill-defined enterprises in AI Cognitive Science. basic scientific question we seek answer is: “What are trade-offs between different ways that systems might be structured?” These depend large part on what kinds tasks environment a system operates under (niche space), also aspects design space deem architectural. In CoSy have tried several ways. First, by thinking about requirements arise from our particular scenarios (parts niche space). Second, building follow well-defined architectural rules, using these carry out experiments variations those rules. Third, insights improve understanding choices, i.e. partial designs. Our objective has not been come up with just another robot architecture, but instead try make some small steps forward new science architectures.

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