Global ETD Search

1	Neural-Symbolic Integration / Neuro-Symbolische Integration Bader, Sebastian 15 December 2009 (has links) (PDF) In this thesis, we discuss different techniques to bridge the gap between two different approaches to artiﬁcial intelligence: the symbolic and the connectionist paradigm. Both approaches have quite contrasting advantages and disadvantages. Research in the area of neural-symbolic integration aims at bridging the gap between them. Starting from a human readable logic program, we construct connectionist systems, which behave equivalently. Afterwards, those systems can be trained, and later the reﬁned knowledge be extracted. Neural-Symbolic Integration Neural Networks Logic Programs Rule Extraction Rule Embedding Rule Refinement Neuro-Symbolische Integration Neuronale Netze Logische Programme Regelextraktion Regeleinbettung Regelverfeinerung ddc:004 rvk:ST 301
2	Neural-Symbolic Integration Bader, Sebastian 05 October 2009 (has links) In this thesis, we discuss different techniques to bridge the gap between two different approaches to artiﬁcial intelligence: the symbolic and the connectionist paradigm. Both approaches have quite contrasting advantages and disadvantages. Research in the area of neural-symbolic integration aims at bridging the gap between them. Starting from a human readable logic program, we construct connectionist systems, which behave equivalently. Afterwards, those systems can be trained, and later the reﬁned knowledge be extracted. info:eu-repo/classification/ddc/004 ddc:004
3	Evaluation Functions in General Game Playing Michulke, Daniel 24 July 2012 (has links) (PDF) While in traditional computer game playing agents were designed solely for the purpose of playing one single game, General Game Playing is concerned with agents capable of playing classes of games. Given the game's rules and a few minutes time, the agent is supposed to play any game of the class and eventually win it. Since the game is unknown beforehand, previously optimized data structures or human-provided features are not applicable. Instead, the agent must derive a strategy on its own. One approach to obtain such a strategy is to analyze the game rules and create a state evaluation function that can be subsequently used to direct the agent to promising states in the match. In this thesis we will discuss existing methods and present a general approach on how to construct such an evaluation function. Each topic is discussed in a modular fashion and evaluated along the lines of quality and efficiency, resulting in a strong agent. Agent Spiele Allgemeine Spiele Künstliche Intelligenz Bewertungsfunktionen Zustandsbewertung Heuristik Merkmale Neuronale Netze Neuro-Symbolische Integration Agent Games General Game Playing GGP Artificial Intelligence evaluation function state evaluation heuristic features neural networks neuro-symbolic integration ddc:003 ddc:004 ddc:006 rvk:ST 324 Heuristik Merkmal Agent <Künstliche Intelligenz> Spieltheorie
4	Evaluation Functions in General Game Playing Michulke, Daniel 22 June 2012 (has links) While in traditional computer game playing agents were designed solely for the purpose of playing one single game, General Game Playing is concerned with agents capable of playing classes of games. Given the game's rules and a few minutes time, the agent is supposed to play any game of the class and eventually win it. Since the game is unknown beforehand, previously optimized data structures or human-provided features are not applicable. Instead, the agent must derive a strategy on its own. One approach to obtain such a strategy is to analyze the game rules and create a state evaluation function that can be subsequently used to direct the agent to promising states in the match. In this thesis we will discuss existing methods and present a general approach on how to construct such an evaluation function. Each topic is discussed in a modular fashion and evaluated along the lines of quality and efficiency, resulting in a strong agent.:Introduction Game Playing Evaluation Functions I - Aggregation Evaluation Functions II - Features General Evaluation Related Work Discussion info:eu-repo/classification/ddc/003 ddc:003 info:eu-repo/classification/ddc/004 ddc:004 info:eu-repo/classification/ddc/006 ddc:006

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