Browsing by Author "Trigo, Paulo"
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- Agent inferencing meets the semantic webPublication . Trigo, Paulo; Coelho, HelderWe provide all agent; the capability to infer the relations (assertions) entailed by the rules that, describe the formal semantics of art RDFS knowledge-base. The proposed inferencing process formulates each semantic restriction as a rule implemented within a, SPARQL query statement. The process expands the original RDF graph into a fuller graph that. explicitly captures the rule's described semantics. The approach is currently being explored in order to support descriptions that follow the generic Semantic Web Rule Language. An experiment, using the Fire-Brigade domain, a small-scale knowledge-base, is adopted to illustrate the agent modeling method and the inferencing process.
- Comparison of distributed computing approaches to complexity of n-gram extractionPublication . Aubakirov, Sanzhar; Trigo, Paulo; Ahmed-Zaki, DarhanIn this paper we compare different technologies that support distributed computing as a means to address complex tasks. We address the task of n-gram text extraction which is a big computational given a large amount of textual data to process. In order to deal with such complexity we have to adopt and implement parallelization patterns. Nowadays there are several patterns, platforms and even languages that can be used for the parallelization task. We implemented this task on three platforms: (1) MPJ Express, (2) Apache Hadoop, and (3) Apache Spark. The experiments were implemented using two kinds of datasets composed by: (A) a large number of small files, and (B) a small number of large files. Each experiment uses both datasets and the experiment repeats for a set of different file sizes. We compared performance and efficiency among MPJ Express, Apache Hadoop and Apache Spark. As a final result we are able to provide guidelines for choosing the platform that is best suited for each kind of data set regarding its overall size and granularity of the input data.
- Decisions with multiple simultaneous goals and uncertain causal effectsPublication . Trigo, Paulo; Coelho, HelderA key aspect of decision-making in a disaster response scenario is the capability to evaluate multiple and simultaneously perceived goals. Current competing approaches to build decision-making agents are either mental-state based as BDI, or founded on decision-theoretic models as MDP. The BDI chooses heuristically among several goals and the MDP searches for a policy to achieve a specific goal. In this paper we develop a preferences model to decide among multiple simultaneous goals. We propose a pattern, which follows a decision-theoretic approach, to evaluate the expected causal effects of the observable and non-observable aspects that inform each decision. We focus on yes-or-no (i.e., pursue or ignore a goal) decisions and illustrate the proposal using the RoboCupRescue simulation environment.
- Formação de equipa para combate a incêndio urbanoPublication . Araújo, Paulo; Trigo, Paulo; Respício, Ana; Lopes, CarlosNeste artigo descreve-se uma abordagem para dimensionar uma equipa de bombeiros para combate a incêndio urbano em ambiente de simulação. A simulação foi realizada no ambiente RoboCupRescue que combina, num mesmo espaço geográfico (e.g. cidade), a evolução de uma catástrofe (e.g. incêndio urbano) e a actuação dos meios (humanos) que visam mitigar os efeitos dessa catástrofe. A abordagem seguida permite determinar o número mínimo de elementos a constituir numa equipa de bombeiros para extinguir um determinado incêndio. Utilizou-se um processo de exploração de conhecimento a partir de um conjunto de treino para construir uma árvore de decisão, recorrendo ao algoritmo de classificação ID3. O conjunto de treino foi obtido a partir da simulação de diferentes situações de incêndio usando o espaço geográfico (mapa) da cidade japonesa de Kobe. São analisados os resultados da avaliação das regras geradas e apresentam-se algumas conclusões sobre os factores que influenciam o critério de formação das equipas.
- A hybrid approach to multi-agent decision-makingPublication . Trigo, Paulo; Coelho, HélderIn the aftermath of a large-scale disaster, agents' decisions derive from self-interested (e.g. survival), common-good (e.g. victims' rescue) and teamwork (e.g. fire extinction) motivations. However, current decision-theoretic models are either purely individual or purely collective and find it difficult to deal with motivational attitudes; on the other hand, mental-state based models find it difficult to deal with uncertainty. We propose a hybrid, CvI-JI, approach that combines: i) collective 'versus' individual (CvI) decisions, founded on the Markov decision process (MDP) quantitative evaluation of joint-actions, and ii)joint-intentions (JI) formulation of teamwork, founded on the belief-desire-intention (BDI) architecture of general mental-state based reasoning. The CvI-JI evaluation explores the performance's improvement
- Multi-agent simulation of electricity markets economically-motivated decision-makingPublication . Trigo, Paulo; Sousa, Jorge A. M.; Marques, PauloThe key motivation for this research is the perception that within a near future the electricity market will be composed of individuals that may simultaneously undertake the roles of consumers, producers and traders of electricity. Those individuals are economically motivated “prosumer” (producer-consumer) agents that not only consume, but can also produce, store and trade electricity. Therefore, as the prosumer agents follow their economically motivated goals (e.g., aiming for profit) they will also experience different forms of power (e.g., market power) and their social relations (e.g., dependencies) will mutually influence their decisionmaking processes. This paper describes the most relevant aspects of a simulation tool that provides (human and virtual) prosumer agents na interactive and real-time game-like environment where they can explore (long-term and short-term) strategic behaviour and experience the effects of power and social influence in their decisionmaking processes. The work on the quantitative description of power and influence concepts, is described and details are provided throughout an illustrative example.
- Parallel implementation of force algorithms for graph visualizationPublication . Zhansultan, Abenov; Sanzhar, Aubakirov; Trigo, PauloIn this paper we select some graph generate-and-render algorithms and evaluate their performance. The experimental results ground our proposal of a parallelized version of an algorithm (the Force Atlas 2) and the corresponding performance analysis. Our work resorts to graph visualization tools such as D3.js, jgraph, NetworkX, Gephi, and sigma.js. We analyze how to use those tools, their advantages and disadvantages and compare their performance. Since each of those tools use their own algorithms, we also conducted a comparative review of graph visualization algorithms. We reviewed algorithms such as FA (Force Atlas), FA2 (Force Atlas 2), FR (Fruchterman & Reingold), LinLog and Dijkstra (Dijkstra's algorithm). The different algorithms were experimentally compared on the same data. The experiments enabled to build a performance ranked perspective. The fastest algorithm was chosen, and experiments were carried out to optimize the rate of generation of graph coordinates by introducing parallel computations during the generation of graph coordinates. During the experiments, the best visualization algorithm for Force Atlas 2 graphs was identified and selected. This algorithm was parallelized, and we achieved a relevant speedup ratio around 26.7% and parallel efficiency around 30%.
- (Virtual) Agents for running electricity marketsPublication . Trigo, Paulo; Marques, Paulo; Coelho, HelderThis paper describes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The artificial market, named TEMMAS (The Electricity Market Multi-Agent Simulator), explores the integration of two design constructs: (i) the specification of the environmental physical market properties and (ii) the specification of the decision-making (deliberative) and reactive agents. TEMMAS is materialized in an experimental setup involving distinct power generator companies that operate in the market and search for the trading strategies that best exploit their generating units' resources. The experimental results show a coherent market behavior that emerges from the overall simulated environment.