Navegando por Autor "CABALAR, P."

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An investigation of actions, change and space
(2013-07-10) Paulo Santos; CABALAR, P.
This work investigates the spatial knowledge and automated solution of a domain composed of non-trivial objects such as strings and holed objects. Copyright © 2013, Association for the Advancement of Artificial Intelligence. All rights reserved.
An investigation of actions, change, space within a hole-loop dichotomy
(2013-05-27) Paulo Santos; CABALAR, P.
© COMMONSENSE 2013 - 11th International Symposium on Logical Formalizations of Commonsense Reasoning. All rights reserved.This work investigates the spatial knowledge of a domaincomposed of non-trivial objects such as strings and holed objects. To this aim, we consider the formalisation of puzzlelike examples as the starting point for the development ofKnowledge Representation systems. The present paper concentrates on the representation of "loops" (or loop-like regions) that can be formed by a flexible string, and that mayplay an essential part in the solution of physical problems involving strings.
Heuristics, Answer Set Programming and Markov Decision Process for Solving a Set of Spatial Puzzles*
(2022-03-05) DOS SANTOS, T. F.; SANTOS, P. E.; FERREIRA, L. A; Reinaldo Bianchi; CABALAR, P.
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.Spatial puzzles composed of rigid objects, flexible strings and holes offer interesting challenges for reasoning about spatial entities that are common in the human daily-life’s activities. This motivates the use of spatial puzzles as domains of study in this work. The goal of this paper is to investigate the automated solution of this kind of problems by extending an algorithm that combines Answer Set Programming (ASP) with Markov Decision Process (MDP) and Reinforcement Learning (RL), called oASP(MDP). This method is capable of constructing the set of domain states online, i.e., while the agent interacts with a changing environment. The aim of the extension proposed in this work is to add heuristics as a mechanism to accelerate the learning process, resulting in the main contribution of this paper: the Heuristic oASP(MDP) (HoASP(MDP)) algorithm. Experiments were performed on deterministic, non-deterministic and non-stationary versions of the puzzles. Results show that the proposed approach can considerably accelerate the learning process, outperforming other state-of-the-art methods.
Holes, knots and shapes: a spatial ontology of a puzzle
(2011-09-27) Paulo Santos; CABALAR, P.
In this paper we propose a spatial ontology for reasoning about holes, rigid objects and strings, taking a classical puzzle as a motivating example. In this ontology the domain is composed of spatial regions whereby a theory about holes is defined over a mereological basis. We also assume primitives for representing shapes of objects (including the string). From these primitives we propose a sufficient condition for object's penetrability through holes. Additionally, a string is represented as a data structure defined upon a sequence of sections limited by points where the string crosses itself or points where it passes through a hole. This paper first appeared as as technical report [7] and presents the initial framework that was further developed in [8, 2].
Holes, knots and shapes: A spatial ontology of a puzzle
(2007-03-26) Paulo Santos; CABALAR, P.
In this paper we propose a spatial ontology for reasoning about holes, rigid objects and strings, taking a classical puzzle as a motivating example. In this ontology the domain is composed of spatial regions whereby a theory about holes is defined over a mereological basis. We also assume primitives for representing shapes of objects (including the string). From these primitives we propose a sufficient condition for object's penetrability through holes. Additionally, a string is represented as a data structure defined upon a sequence of sections limited by points where the string crosses itself or points where it passes through a hole. Copyright © 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Solving a spatial puzzle using answer set programming integrated with Markov decision process
(2018-12-05) SANTOS, T. F.; Paulo Santos; FERREIRA, L.; Reinaldo Bianchi; CABALAR, P.
© 2018 IEEE.Spatial puzzles are interesting domains to investigate problem solving, since the reasoning processes involved in reasoning about spatial knowledge is one of the essential items for an agent to interact in the human environment. With this in mind, the goal of this work is to investigate the knowledge representation and reasoning process related to the solution of a spatial puzzle, the Fisherman's Folly, composed of flexible string, rigid objects and holes. To achieve this goal, the present paper uses heuristics (obtained after solving a relaxed version of the puzzle) to accelerate the learning process, while applying a method that combines Answer Set programming (ASP) with Reinforcement learning (RL), the oASP(MDP) algorithm, to find a solution to the puzzle. ASP is the logic language chosen to build the set of states and actions of a Markov Decision Process (MDP) representing the domain, where RL is used to learn the optimal policy of the problem.
Spatial reasoning about string loops and holes in temporal asp
(2020-09-12) CABALAR, P.; Paulo Santos
© 2020 17th International Conference on Principles of Knowledge Representation and Reasoning, KR 2020. All rights reserved.This paper introduces a new formalism for the automated solution of spatial scenarios involving strings and holed objects. In particular, we revisit a previous formalisation that allows string loops to be treated as holes, but make a substantial modification by removing a previous limitation that prevented a string to cross its own loops. The formalisation introduced in the present paper relies on string segments as basic entities and achieves a greater degree of elaboration tolerance by using inertia to describe those parts of the physical scenario that are unaffected by a given action. As a representation language, we have used Temporal Answer Set Programming since it provides a simple and natural way to deal with time and inertia while, at the same time, it is accompanied by the automated tool telingo that allows a systematic testing of the effects of any sequence of actions. As an illustrative example, we have studied the African Ring puzzle, a problem involving loops crossed by a unique string, and provided the first formalisation of its solution, to the best of our knowledge.
The knowledge of knots: an interdisciplinary literature review
(2019-10-02) Paulo Santos; CABALAR, P.; CASATI, R.
© 2019, © 2019 Taylor & Francis.Knots can be found and used in a variety of situations in the 3D world, such as in vines, in the DNA, polymer chains, electrical wires, in mountaineering, seamanship and when ropes or other flexible objects are involved for exerting forces and holding objects in place. Research on knots as topological entities has contributed with a number of findings, not only of interest to pure mathematics, but also to statistical mechanics, quantum physics, genetics, and chemistry. Yet, the cognitive (or algorithmic) aspects involved in the act of tying a knot are a largely uncharted territory. This paper presents a review of the literature related to the investigation of knots from the topological, physical, cognitive and computational (including robotics) standpoints, aiming at bridging the gap between pure mathematical work on knot theory and macroscopic physical knots, with an eye to applications and modeling.