P-SPACE: A program for simulating spatial behavior in small groups

Quera, Vicenç; Solanas, Antoni; Salafranca, Lluís; Beltran, Francesc S.; Herrando, Salvador

doi:10.3758/bf03200801

Cited by 7 publications

(4 citation statements)

References 9 publications

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“…In this respect, our approach is similar to Artificial Life's [11,5,12,16,17]. AL postulates that the mechanisms underlying adaptive behavior must necessarily be studied and conceived in situ, in other words, the goals the agent is trying for and the opportunities the environment affords for doing so must be accounted for.…”

Section: Bottom-up and Top-down Approaches To Interpreting Perceived mentioning

confidence: 99%

“…In contrast, a second type of computational model arises from the Artificial Life (AL) paradigm [e.g. ; 11,5,12,16,17]. This more recent approach takes an evolutionist, situated and bottom-up perspective in which the data furnished by the environment have the priority for studying the adaptive capacities of living beings and robots.…”

Section: Some Existing Models For Interpreting Perceived Actionsmentioning

confidence: 99%

“…Initially, the agents move according to a few simple pre-specified rules (i.e., agents may walk at random, chase each other, approach and leave all the other agents,...) [16,17]. However, as the simulation progresses and they learn how to predict other agents' actions through generalization, they become capable of reacting to or even anticipating these actions.…”

Section: Adaptation and Predictionmentioning

confidence: 99%

“…For more sophisticated simulation of action interpretation using our ACACIA model, we are currently developing computer models 1) of the probability of perceived events and properties in the situation, and 2) to refine the simple rules defining basic displacements in space (i.e. walking at random, chasing each other, approaching and leaving all the other agents, as in the P-Space model) [16,17].…”

Section: Building the Knowledge Networkmentioning

confidence: 99%

See 3 more Smart Citations

Contextual Categorization: A Mechanism Linking Perception and Knowledge in Modeling and Simulating Perceived Events as Actions

Zibetti

Quera

Beltran

et al. 2001

Modeling and Using Context

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Abstract. The specific objective of this paper is to introduce the computer model ACACIA (Action by Contextually Automated Categorizing Interactive Agents) capable of simulating the way in which context is taken into account for the interpretation of perceived actions elaborated by a number of autonomous moving agents in a bidimensional space. With this in mind, we will examine some different modeling approaches in Artificial Intelligence and Artificial Life and emphasize the strong and weak points of each approach in relation to the set of issues addressed by our theory based on Contextual Categorization. Second, we provide a theoretical explanation of how contextual categorization accounts for temporal and environmental context to interpret ongoing situations in terms of perceived action. Finally, we describe the computer implementation of ACACIA, and we propose a preliminary simulation of a simple situation using StarLogo software.

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Section: Bottom-up and Top-down Approaches To Interpreting Perceived mentioning

confidence: 99%