Search results for "ComputingMethodologies_ARTIFICIALINTELLIGENCE"
showing 10 items of 46 documents
Advances in Practical Applications of Agents, Multi-Agent Systems, and Sustainability: The PAAMS Collection
2015
This volume presents the papers that have been accepted for the 2015 special sessions of the 13th International Conference on Practical Applications of Agents and Multi-Agent Systems, held at University of Salamanca, Spain, at 3rd-5th June, 2015: Agents Behaviours and Artificial Markets (ABAM); Agents and Mobile Devices (AM); Multi-Agent Systems and Ambient Intelligence (MASMAI); Web Mining and Recommender systems (WebMiRes); Learning, Agents and Formal Languages (LAFLang); Agent-based Modeling of Sustainable Behavior and Green Economies (AMSBGE); Emotional Software Agents (SSESA) and Intelligent Educational Systems (SSIES). The volume also includes the paper accepted for the Doctoral Conso…
3D models of humanoid soccer robot in USAR sim and robotics studio simulators
2008
This paper describes our experience in the simulation of humanoid soccer robots using two general purposes 3D simulators, namely USARSim and Microsoft Robotics Studio. We address the problem of the simulation of a soccer match among two teams of small humanoid robots in the RoboCup Soccer Kid-Size Humanoid competitions. The paper reports the implementation of the virtual models of the Robovie-M humanoid robot platform in the two simulators. Robovie-M was the robot used by our team "Artisti" in the RoboCup 2006 competitions. This paper focuses on the procedures needed to implement the virtual models of the robot and in the details of the models. We describe experiments assessing the feasibi…
Towards a multilevel ant colony optimization
2014
Masteroppgave i Informasjons- og kommunikasjonsteknologi IKT590 Universitetet i Agder 2014 Ant colony optimization is a metaheuristic approach for solving combinatorial optimization problems which belongs to swarm intelligence techniques. Ant colony optimization algorithms are one of the most successful strands of swarm intelligence which has already shown very good performance in many combinatorial problems and for some real applications. This thesis introduces a new multilevel approach for ant colony optimization to solve the NP-hard problems shortest path and traveling salesman. We have reviewed different elements of multilevel algorithm which helped us in construction of our proposed mu…
Prey-predator strategies in a multiagent system
2006
This paper describes the prey-predator multiagent system which can be considered as an abstraction of more complex real-world models. Both the prey and the predators are considered as autonomous agents with their own behaviors and perception of the environment. In particular, we propose a simulator which lets study different strategies such as cooperation and individualism. An extensive experiment has been carried out in order to prove the effectiveness of the latter.
The PASSI and Agile PASSI MAS Meta-models Compared with a Unifying Proposal
2005
A great number of processes for multi-agent systems design have been presented in last years to support the different approaches to agent-oriented design; each process is specific for a particular class of problems and it instantiates a specific MAS meta-model. These differences produce inconsistences and overlaps: a MAS meta-model may define a term not referred by another, or the same term can be used with a different meaning. We think that the lack of a standardization may cause a significant delay to the diffusion of the agent paradigm outside research context. Working for this unification goal, it is also necessary to define in unambiguous way the terms of the agent model and their rela…
Soccer analyses by means of artificial neural networks, automatic pass recognition and Voronoi-cells: An approach of measuring tactical success.
2015
Success in a soccer match is usually measured by goals. However, in order to yield goals, successful tactical pre-processing is necessary. If analyzing a match with the focus on “success”, promising tactical activities including vertical passes with control win in the opponent’s penalty area have to be the focus. Whether or not a pass is able to crack the opponent’s defence depends on the tactical formations of both the opponent’s defence and the own offence group.
AGI and Machine Consciousness
2012
This review discusses some of main issues to be addressed to design a conscious AGI agent: the agent’s sense of the body, the interaction with the environment, the agent’s sense of time, the free will of the agent, the capability for the agent to have some form of experience, and finally the relationship between consciousness and creativity.
Recursive and bargaining values
2021
Abstract We introduce two families of values for TU-games: the recursive and bargaining values. Bargaining values are obtained as the equilibrium payoffs of the symmetric non-cooperative bargaining game proposed by Hart and Mas-Colell (1996). We show that bargaining values have a recursive structure in their definition, and we call this property recursiveness. All efficient, linear, and symmetric values that satisfy recursiveness are called recursive values. We generalize the notions of potential, and balanced contributions property, to characterize the family of recursive values. Finally, we show that if a time discount factor is considered in the bargaining model, every bargaining value h…
Cryptanalysis of Knapsack Cipher Using Ant Colony Optimization
2018
Ant Colony Optimization is a search metaheuristic inspired by the behavior of real ant colonies and shown their effectiveness, robustness to solve a wide variety of complex problems. In this paper, we present a novel Ant Colony Optimization (ACO) based attack for cryptanalysis of knapsack cipher algorithm. A Cipher-text only attack is used to discover the plaintext from the cipher-text. Moreover, our approach allows us to break knapsack cryptosystem in a minimum search space when compared with other techniques. Experimental results prove that ACO can be used as an effective tool to attack knapsack cipher.
Optimizing PolyACO Training with GPU-Based Parallelization
2016
A central part of Ant Colony Optimisation (ACO) is the function calculating the quality and cost of solutions, such as the distance of a potential ant route. This cost function is used to deposit an opportune amount of pheromones to achieve an apt convergence, and in an active ACO implementation a significant part of the runtime is spent in this part of the code. In some cases, the cost function accumulates up towards 94 % in its run time making it a performance bottle neck.