http://popups.lib.uliege.be/1373-5411/index.php?id=628 Index terms fr 0 http://popups.lib.uliege.be/1373-5411/index.php?id=2669 The use of games as testbeds for research projects in the Artificial Intelligence (AI) field is a tradition. Some classic board and card games such as Go, Chess and Checkers were and are extensively used. However, AI researchers are beginning to explore the use of real-time interactive computer games in their research, making this an interesting field to experiment and explore. This paper presents the SCORE project (Simulator for COgnitive agent's behavioR), where we use a Belief-Desire-Intention (BDI) agent specification formalism called X-BDI, applied to a game environment called, Unreal Toumament (UT). This paper also presents some aspects regarding AI and agent technology applied to interactive computer games, with emphasis in the application of cognitive agent modelling applied to game characters Thu, 29 Aug 2024 16:44:27 +0200 Tue, 08 Oct 2024 17:21:51 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=2669 http://popups.lib.uliege.be/1373-5411/index.php?id=920 In real condition, elements form sets whose delimitation is vague, thus defining fuzzy sets in Zadeh's acception or fluids sets according to Gentilhomme's definition. Any system characterized by uncontrollability and disorder in which the least changed in its status at a certain moment rapidly leads to important changes in the status measured at a later moment can be defined as a chaotic system. The interdisciplinary study of chaotic system has become a science of complexity or the science of the chaos. Science has always searched the order in a chaotic universe and the science of the chaos uses a geometry named fractal; fractals are defined as a form at which fractal dimension surpassed its topologic dimension or as any form at which the parts have as many details as the whole or as forms which are strictly self-similar and not statistically self-similar. The notion of information necessary involves the notion of order and the notion of order involves the rationality of system as through the relation information shows how rationally organized the elements of the system are and what rational functionality they fulfill within the order which defines the system. By introducing the concept of structural-diachronic cell associate whit the elementary amount of information (the bit) the paper interprets the concept of information in a fractal manner of maximal generality, in the sense that any fraction of the bit is a bit in itself, the structural-diachronic cells being strictly self similar. The fractal interpretation of the concept of information is the theoretical support of the Basis of Universal Knowledge Similar to the human brain. Mon, 01 Jul 2024 14:07:58 +0200 Tue, 08 Oct 2024 14:38:05 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=920 http://popups.lib.uliege.be/1373-5411/index.php?id=626 A two-level processing scheme for real-time image understanding is proposed, where an example-based (or case-based) reasoning in neural AI systems is introduced. The system has two levels; Component Level and Structure Level. At the component level, an elementary pattern recognition is performed as in the conventional pattern recognition, while the syntax pattern recognition is done at the structure level. Both levels are essentially time-consuming (theoretically, NP-complete each). The pattern recognition assisted by syntax recognition reduces the total complexity of processes, and the system can perform a real-time image understanding, when the VLSI chips are introduced. As a result, we show a reasonable real-time image understanding scheme by introducing neural pattern recognition at the component level and a case-based AI technique at the structure level. Fri, 28 Jun 2024 15:24:01 +0200 Tue, 08 Oct 2024 14:06:02 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=626 http://popups.lib.uliege.be/1373-5411/index.php?id=1798 The management of industrial systems involves decision making with respect to complex processes that are often stochastic in nature. Simulation is frequently the only effective mean to model the complexity of such industrial processes. Simulation enables detailed scenario testing and, thus, is well suited for "what if" analysis. However, industrial users often need to solve inverse problems, such as optimization or decision analysis, which cannot be handled by simulation alone. This paper proposes the integrated use of simulation and Artificial Intelligence techniques in hybrid system architectures for advanced industrial problem solving. Hybrid Decision Support Systems (DSSs), combine the complementary strengths of different techniques for integrated forecasting ,modeling, and optimization. Tue, 16 Jul 2024 15:51:31 +0200 Tue, 16 Jul 2024 15:51:42 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=1798