The adversarial character of real-time strategy (RTS) games is one of the main sources of uncertainty within this domain. Since players lack exact knowledge about their opponent's actions, they need a reasonable r...
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The adversarial character of real-time strategy (RTS) games is one of the main sources of uncertainty within this domain. Since players lack exact knowledge about their opponent's actions, they need a reasonable representation of alternative possibilities and their likelihood. In this article we propose a method of predicting the most probable combination of units produced by the opponent during a certain time period. We employ a logic programming paradigm called answer set programming, since its semantics is well suited for reasoning with uncertainty and incomplete knowledge. In contrast with typical, purely probabilistic approaches, the presented method takes into account the background knowledge about the game and only considers the combinations that are consistent with the game mechanics and with the player's partial observations. Experiments, conducted during different phases of StarCraft: BroodWar and Warcraft III: The Frozen Throne games, show that the prediction accuracy for time intervals of 1-3 min seems to be surprisingly high, making the method useful in practice. Root-mean-square error grows only slowly with increasing prediction intervals-almost in a linear fashion.
A number of different Fuzzy answer set programming (FASP) formalisms have been proposed in the last years, which all differ in the language extensions they support. In this paper we investigate the expressivity of the...
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A number of different Fuzzy answer set programming (FASP) formalisms have been proposed in the last years, which all differ in the language extensions they support. In this paper we investigate the expressivity of these frameworks. Specifically we show how a variety of constructs in these languages can be implemented using a considerably simpler core language. These simulations are important as a compact and simple language is easier to implement and to reason about, while an expressive language offers more options when modeling problems. (C) 2012 Elsevier Inc. All rights reserved.
In this survey, we present an overview on (Modal) Temporal Logic programming in view of its application to Knowledge Representation and Declarative Problem Solving. The syntax of this extension of logic programs is th...
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In this survey, we present an overview on (Modal) Temporal Logic programming in view of its application to Knowledge Representation and Declarative Problem Solving. The syntax of this extension of logic programs is the result of combining usual rules with temporal modal operators, as in Linear-time Temporal Logic (LTL). In the paper, we focus on the main recent results of the non-monotonic formalism called Temporal Equilibrium Logic (TEL) that is defined for the full syntax of LTL but involves a model selection criterion based on Equilibrium Logic, a well known logical characterization of answer set programming (ASP). As a result, we obtain a proper extension of the stable models semantics for the general case of temporal formulas in the syntax of LTL. We recall the basic definitions for TEL and its monotonic basis, the temporal logic of Here-and-There (THT), and study the differences between finite and infinite trace length. We also provide further useful results, such as the translation into other formalisms like Quantified Equilibrium Logic and Second-order LTL, and some techniques for computing temporal stable models based on automata constructions. In the remainder of the paper, we focus on practical aspects, defining a syntactic fragment called (modal) temporal logic programs closer to ASP, and explaining how this has been exploited in the construction of the solver telingo, a temporal extension of the well-known ASP solver clingo that uses its incremental solving capabilities.
The Artificial Intelligence (AI) has taken a leading role in many activities which used to be made "by hand";one of them is the musical composition. Such task now has another alternative implementation, thro...
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The Artificial Intelligence (AI) has taken a leading role in many activities which used to be made "by hand";one of them is the musical composition. Such task now has another alternative implementation, through the support of software that can compose different musical genres to the point where a computer can compose pieces with some autonomy. This paper proposes Armin, a system dedicated to the electronic trance music composition. Armins aim is to provide a trance music composition to serve as a template or a base audio file, ready to add more instruments in a mastering (remastering) production Additionally, it seeks to enable greater collaboration between a machine and a human, both seen as musical composers.
answer set programming (ASP) is a prominent knowledge representation language with roots in logic programming and non-monotonic reasoning. Biennial ASP competitions are organized in order to furnish challenging benchm...
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answer set programming (ASP) is a prominent knowledge representation language with roots in logic programming and non-monotonic reasoning. Biennial ASP competitions are organized in order to furnish challenging benchmark collections and assess the advancement of the state of the art in ASP solving. In this paper, we report on the design and results of the Seventh ASP Competition, jointly organized by the University of Calabria (Italy), the University of Genova (Italy), and the University of Potsdam (Germany), in affiliation with the 14th International Conference on Logic programming and Non-Monotonic Reasoning (LPNMR 2017).
We present a method employing answer set programming in combination with Approximate Model Counting for fast and accurate calculation of error propagation probabilities in digital circuits. By an efficient problem enc...
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We present a method employing answer set programming in combination with Approximate Model Counting for fast and accurate calculation of error propagation probabilities in digital circuits. By an efficient problem encoding, we achieve an input data format similar to a Verilog netlist so that extensive preprocessing is avoided. By a tight interconnection of our application with the underlying solver, we avoid iterating over fault sites and reduce calls to the solver. Several circuits were analyzed with varying numbers of considered cycles and different degrees of approximation. Our experiments show, that the runtime can be reduced by approximation by a factor of 91, whereas the error compared to the exact result is below 1%.
The input language of the answerset solver clingo is based on the definition of a stable model proposed by Paolo Ferraris. The semantics of the ASP-Core language, developed by the ASP Standardization Working Group, u...
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The input language of the answerset solver clingo is based on the definition of a stable model proposed by Paolo Ferraris. The semantics of the ASP-Core language, developed by the ASP Standardization Working Group, uses the approach to stable models due to Wolfgang Faber, Nicola Leone, and Gerald Pfeifer. The two languages are based on different versions of the stable model semantics, and the ASP-Core document requires, "for the sake of an uncontroversial semantics," that programs avoid the use of recursion through aggregates. In this paper we prove that the absence of recursion through aggregates does indeed guarantee the equivalence between the two versions of the stable model semantics, and show how that requirement can be relaxed without violating the equivalence property.
We describe an approach to modeling biological networks by action languages via answer set programming. To this end, we propose an action language for modeling biological networks, building on previous work by Baral e...
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We describe an approach to modeling biological networks by action languages via answer set programming. To this end, we propose an action language for modeling biological networks, building on previous work by Baral et al. We introduce its syntax and semantics along with a translation into answer set programming, an efficient Boolean Constraint programming Paradigm. Finally, we describe one of its applications, namely, the sulfur starvation response-pathway of the model plant Arabidopsis thaliana and sketch the functionality of our system and its usage.
answer set programming (ASP) is a well-established paradigm of declarative programming that has been developed in the field of logic programming and non-monotonic reasoning. Advances in ASP solving technology are cust...
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answer set programming (ASP) is a well-established paradigm of declarative programming that has been developed in the field of logic programming and non-monotonic reasoning. Advances in ASP solving technology are customarily assessed in competition events, as it happens for other closely related problem solving areas such as Boolean Satisfiability, Satisfiability Modulo Theories, Quantified Boolean Formulas, Planning, etc. This paper reports about the fifth edition of the ASP Competition by covering all aspects of the event, ranging from the new design of the competition to an in-depth analysis of the results. The paper comprises also additional analyses that were conceived for measuring the progress of the state of the art, as well as for studying aspects orthogonal to solving technology, such as the effects of modeling. A detailed picture of the progress of the state of the art in ASP solving is drawn, and the ASP Competition is located in the spectrum of related events. (C) 2015 Elsevier B.V. All rights reserved.
In this paper, we introduce an argumentation approach which takes an extended logic program as input and gives a set of arguments with the respective disagreements among them as output. We establish the notion of an a...
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In this paper, we introduce an argumentation approach which takes an extended logic program as input and gives a set of arguments with the respective disagreements among them as output. We establish the notion of an argument under the Well-Founded semantics and Stable semantics inferences, allowing us to identify arguments with stratified programs as support, even when the input for the argument engine is a non-stratified program. We propose a set of rationality postulates for argument-based systems under extended logic programs, which are based on a definition of closure for a set of clauses that considers the well-known Gelfond-Lifschitz reduction. We establish the conditions under which our approach satisfies these principles. In addition, we present a standalone argumentation-tool based on the XSB system which implements our argumentation approach. (C) 2015 Elsevier Inc. All rights reserved.
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