ACoPla: a Multiagent Simulator to Study Individual Strategies in Dynamic Situations
One important issue in multi-agent systems is how to define agents’ interaction strategies in dynamic open environments. Generally, agents’ behaviors, such as being cooperative/altruistic or competitive/adversarial, are defined a priori by their creators. However, this is a weak premise when conside...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Ediciones Universidad de Salamanca
2018-12-01
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| Series: | Advances in Distributed Computing and Artificial Intelligence Journal |
| Subjects: | |
| Online Access: | https://revistas.usal.es/index.php/2255-2863/article/view/18971 |
| _version_ | 1818417502072340480 |
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| author | Ana Cristina BICHARRA GARCIA Adriana Santarosa VIVACQUA |
| author_facet | Ana Cristina BICHARRA GARCIA Adriana Santarosa VIVACQUA |
| author_sort | Ana Cristina BICHARRA GARCIA |
| collection | DOAJ |
| description | One important issue in multi-agent systems is how to define agents’ interaction strategies in dynamic open environments. Generally, agents’ behaviors, such as being cooperative/altruistic or competitive/adversarial, are defined a priori by their creators. However, this is a weak premise when considering interaction among anonymous self-interested agents. Whenever agents meet, there is always a decision to be made: what is the best group interaction strategy? We argue that the answer depends on the amount of information required to make a decision and on the deadline proximity for accomplishing the task in hand. In certain situations, it is to the agents’ advantage to exchange information with others, while in other situations there are no incentives for them to spend time doing so. Understanding effective behaviors according to the decision- making scenario is still an open issue in multi-agent systems. In this paper, we present a multi-agent simulator (ACoPla) to understand the correlations between agents’ interaction strategy, decision-making context and successful task accomplishment rate. Additionally, we develop a case study in the domain of site evacuation to exemplify our findings. Through this study, we detect the types of conditions under which cooperation becomes the preferred strategy, as the environment changes. |
| first_indexed | 2024-12-14T12:07:48Z |
| format | Article |
| id | doaj.art-366a18a14cbd423fa645c8cb701196ba |
| institution | Directory Open Access Journal |
| issn | 2255-2863 |
| language | English |
| last_indexed | 2024-12-14T12:07:48Z |
| publishDate | 2018-12-01 |
| publisher | Ediciones Universidad de Salamanca |
| record_format | Article |
| series | Advances in Distributed Computing and Artificial Intelligence Journal |
| spelling | doaj.art-366a18a14cbd423fa645c8cb701196ba2022-12-21T23:01:50ZengEdiciones Universidad de SalamancaAdvances in Distributed Computing and Artificial Intelligence Journal2255-28632018-12-0172819110.14201/ADCAIJ201872819116229ACoPla: a Multiagent Simulator to Study Individual Strategies in Dynamic SituationsAna Cristina BICHARRA GARCIA0Adriana Santarosa VIVACQUA1Universidade Federal do Estado do Rio de JaneiroUniversidade Federal do Rio de JaneiroOne important issue in multi-agent systems is how to define agents’ interaction strategies in dynamic open environments. Generally, agents’ behaviors, such as being cooperative/altruistic or competitive/adversarial, are defined a priori by their creators. However, this is a weak premise when considering interaction among anonymous self-interested agents. Whenever agents meet, there is always a decision to be made: what is the best group interaction strategy? We argue that the answer depends on the amount of information required to make a decision and on the deadline proximity for accomplishing the task in hand. In certain situations, it is to the agents’ advantage to exchange information with others, while in other situations there are no incentives for them to spend time doing so. Understanding effective behaviors according to the decision- making scenario is still an open issue in multi-agent systems. In this paper, we present a multi-agent simulator (ACoPla) to understand the correlations between agents’ interaction strategy, decision-making context and successful task accomplishment rate. Additionally, we develop a case study in the domain of site evacuation to exemplify our findings. Through this study, we detect the types of conditions under which cooperation becomes the preferred strategy, as the environment changes.https://revistas.usal.es/index.php/2255-2863/article/view/18971agentsemergencymultiagent systemssocial simulationdecision-making strategies |
| spellingShingle | Ana Cristina BICHARRA GARCIA Adriana Santarosa VIVACQUA ACoPla: a Multiagent Simulator to Study Individual Strategies in Dynamic Situations Advances in Distributed Computing and Artificial Intelligence Journal agents emergency multiagent systems social simulation decision-making strategies |
| title | ACoPla: a Multiagent Simulator to Study Individual Strategies in Dynamic Situations |
| title_full | ACoPla: a Multiagent Simulator to Study Individual Strategies in Dynamic Situations |
| title_fullStr | ACoPla: a Multiagent Simulator to Study Individual Strategies in Dynamic Situations |
| title_full_unstemmed | ACoPla: a Multiagent Simulator to Study Individual Strategies in Dynamic Situations |
| title_short | ACoPla: a Multiagent Simulator to Study Individual Strategies in Dynamic Situations |
| title_sort | acopla a multiagent simulator to study individual strategies in dynamic situations |
| topic | agents emergency multiagent systems social simulation decision-making strategies |
| url | https://revistas.usal.es/index.php/2255-2863/article/view/18971 |
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