Computational and Robotic Models of the Hierarchical by Gianluca Baldassarre, Marco Mirolli

By Gianluca Baldassarre, Marco Mirolli

Current robots and different synthetic platforms tend to be in a position to accomplish just one unmarried activity. Overcoming this quandary calls for the improvement of keep an eye on architectures and studying algorithms which may aid the purchase and deployment of a number of diverse talents, which in flip turns out to require a modular and hierarchical association. during this approach, diversified modules can collect various abilities with no catastrophic interference, and higher-level parts of the process can resolve complicated initiatives via exploiting the talents encapsulated within the lower-level modules. whereas computer studying and robotics realize the elemental value of the hierarchical association of habit for construction robots that scale as much as resolve complicated projects, examine in psychology and neuroscience exhibits expanding facts that modularity and hierarchy are pivotal association rules of habit and of the mind. they may even result in the cumulative acquisition of an ever-increasing variety of abilities, which appears to be like a attribute of mammals, and people in particular.

This ebook is a accomplished review of the cutting-edge at the modeling of the hierarchical association of habit in animals, and on its exploitation in robotic controllers. The publication standpoint is very interdisciplinary, that includes types belonging to all appropriate components, together with laptop studying, robotics, neural networks, and computational modeling in psychology and neuroscience. The publication chapters evaluation the authors' latest contributions to the research of hierarchical habit, and spotlight the open questions and so much promising learn instructions. because the contributing authors are one of the pioneers engaging in primary paintings in this subject, the publication covers crucial and topical concerns within the box from a computationally knowledgeable, theoretically orientated viewpoint. The ebook might be of gain to educational and business researchers and graduate scholars in comparable disciplines.

Show description

Read Online or Download Computational and Robotic Models of the Hierarchical Organization of Behavior PDF

Similar artificial intelligence books

Theoretical Foundations of Artificial General Intelligence

This booklet is a set of writings through lively researchers within the box of man-made normal Intelligence, on issues of crucial value within the box. each one bankruptcy makes a speciality of one theoretical challenge, proposes a unique resolution, and is written in sufficiently non-technical language to be comprehensible by means of complex undergraduates or scientists in allied fields.

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

Algorithms more and more run our lives. They locate books, videos, jobs, and dates for us, deal with our investments, and become aware of new medications. progressively more, those algorithms paintings by way of studying from the paths of knowledge we depart in our newly electronic global. Like curious childrens, they detect us, imitate, and test.

Programming Multi-Agent Systems in AgentSpeak using Jason

Jason is an Open resource interpreter for a longer model of AgentSpeak – a logic-based agent-oriented programming language – written in Java™. It permits clients to construct complicated multi-agent platforms which are in a position to working in environments formerly thought of too unpredictable for pcs to deal with.

Reactive Kripke Semantics

This article bargains an extension to the conventional Kripke semantics for non-classical logics via including the concept of reactivity. Reactive Kripke types switch their accessibility relation as we growth within the overview strategy of formulation within the version. this option makes the reactive Kripke semantics strictly better and extra appropriate than the normal one.

Extra info for Computational and Robotic Models of the Hierarchical Organization of Behavior

Example text

Brodley & A. P. ), Proceedings of the eighteenth international conference on machine learning (ICML 2001) (pp. 361–368). San Francisco: Morgan Kaufmann. , Tadepalli, P. (2008). Transfer in variable-reward hierarchical reinforcement learning. Machine Learning, 73, 289–312. , Shimkin, N. (2002). Q-Cut – Dynamic discovery of sub-goals in reinforcement learning. In Machine learning: ECML 2002, 13th European conference on machine learning. Lecture notes in computer science (vol. 2430, pp. 295–306). Berlin: Springer.

Digney, B. (1996). Emergent hierarchical control structures: learning reactive/hierarchical relationships inreinforcement environments. In P. Meas, M. -A. Meyer, J. Pollack, S. W. ), From animals to animats 4: proceedings of the fourth international conference on simulation of adaptive behavior (pp. 363–372). Cambridge: MIT. , Leffler, B. (2009). The adaptive k-meteorologists problems and its application to structure learning and feature selection in reinforcement learning. In A. P. Danyluk, L.

2011b). Mahadevan (2009) provides a thorough account of the use of basis functions in RL. Skill-specific representations can therefore differ in terms of native features, function approximation methods, basis functions, or all of these. For example, 4 Actions similarly have native representations, but we restrict attention to state representations to keep things simple. G. Barto et al. a skill may depend only on a subset of the environment’s full set of native features, the rest being irrelevant to the skill.

Download PDF sample

Rated 4.88 of 5 – based on 42 votes