Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents
Intelligent embodied robots are integrated systems: As they move continuously through their environments, executing behaviors and carrying out tasks, components for low-level and high-level intelligence are integrated in the robot's cognitive system, and cognitive and physical processes combine...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2016-11-01
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| Series: | Frontiers in Robotics and AI |
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| Online Access: | http://journal.frontiersin.org/Journal/10.3389/frobt.2016.00066/full |
| _version_ | 1819089916586360832 |
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| author | Eric Aaron Eric Aaron |
| author_facet | Eric Aaron Eric Aaron |
| author_sort | Eric Aaron |
| collection | DOAJ |
| description | Intelligent embodied robots are integrated systems: As they move continuously through their environments, executing behaviors and carrying out tasks, components for low-level and high-level intelligence are integrated in the robot's cognitive system, and cognitive and physical processes combine to create their behavior. For a modeling framework to enable the design and analysis of such integrated intelligence, the underlying representations in the design of the robot should be dynamically sensitive, capable of reflecting both continuous motion and micro-cognitive influences, while also directly representing the necessary beliefs and intentions for goal-directed behavior. In this paper, a dynamical intention-based modeling framework is presented that satisfies these criteria, along with a hybrid dynamical cognitive agent (HDCA) framework for employing dynamical intentions in embodied agents. This dynamical intention-HDCA (DI-HDCA) modeling framework is a fusion of concepts from spreading activation networks, hybrid dynamical system models, and the BDI (belief-desire-intention) theory of goal-directed reasoning, adapted and employed unconventionally to meet entailments of environment and embodiment. The paper presents two kinds of autonomous agent learning results that demonstrate dynamical intentions and the multi-faceted integration they enable in embodied robots: with a simulated service robot in a grid-world office environment, reactive-level learning minimizes reliance on deliberative-level intelligence, enabling task sequencing and action selection to be distributed over both deliberative and reactive levels; and with a simulated game of Tag, the cognitive-physical integration of an autonomous agent enables the straightforward learning of a user-specified strategy during gameplay, without interruption to the game. In addition, the paper argues that dynamical intentions are consistent with cognitive theory underlying goal-directed behavior, and that DI-HDCA modeling may facilitate the study of emergent behaviors in embodied agents. |
| first_indexed | 2024-12-21T22:15:32Z |
| format | Article |
| id | doaj.art-d0e4fea767a44e2fa7187204fb4f18c8 |
| institution | Directory Open Access Journal |
| issn | 2296-9144 |
| language | English |
| last_indexed | 2024-12-21T22:15:32Z |
| publishDate | 2016-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Robotics and AI |
| spelling | doaj.art-d0e4fea767a44e2fa7187204fb4f18c82022-12-21T18:48:27ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442016-11-01310.3389/frobt.2016.00066205698Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied AgentsEric Aaron0Eric Aaron1Vassar CollegeVassar CollegeIntelligent embodied robots are integrated systems: As they move continuously through their environments, executing behaviors and carrying out tasks, components for low-level and high-level intelligence are integrated in the robot's cognitive system, and cognitive and physical processes combine to create their behavior. For a modeling framework to enable the design and analysis of such integrated intelligence, the underlying representations in the design of the robot should be dynamically sensitive, capable of reflecting both continuous motion and micro-cognitive influences, while also directly representing the necessary beliefs and intentions for goal-directed behavior. In this paper, a dynamical intention-based modeling framework is presented that satisfies these criteria, along with a hybrid dynamical cognitive agent (HDCA) framework for employing dynamical intentions in embodied agents. This dynamical intention-HDCA (DI-HDCA) modeling framework is a fusion of concepts from spreading activation networks, hybrid dynamical system models, and the BDI (belief-desire-intention) theory of goal-directed reasoning, adapted and employed unconventionally to meet entailments of environment and embodiment. The paper presents two kinds of autonomous agent learning results that demonstrate dynamical intentions and the multi-faceted integration they enable in embodied robots: with a simulated service robot in a grid-world office environment, reactive-level learning minimizes reliance on deliberative-level intelligence, enabling task sequencing and action selection to be distributed over both deliberative and reactive levels; and with a simulated game of Tag, the cognitive-physical integration of an autonomous agent enables the straightforward learning of a user-specified strategy during gameplay, without interruption to the game. In addition, the paper argues that dynamical intentions are consistent with cognitive theory underlying goal-directed behavior, and that DI-HDCA modeling may facilitate the study of emergent behaviors in embodied agents.http://journal.frontiersin.org/Journal/10.3389/frobt.2016.00066/fullLearningmachine learningembodimentaction selectionCognitive RoboticsHybrid systems |
| spellingShingle | Eric Aaron Eric Aaron Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents Frontiers in Robotics and AI Learning machine learning embodiment action selection Cognitive Robotics Hybrid systems |
| title | Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents |
| title_full | Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents |
| title_fullStr | Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents |
| title_full_unstemmed | Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents |
| title_short | Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents |
| title_sort | dynamical intention integrated intelligence modeling for goal directed embodied agents |
| topic | Learning machine learning embodiment action selection Cognitive Robotics Hybrid systems |
| url | http://journal.frontiersin.org/Journal/10.3389/frobt.2016.00066/full |
| work_keys_str_mv | AT ericaaron dynamicalintentionintegratedintelligencemodelingforgoaldirectedembodiedagents AT ericaaron dynamicalintentionintegratedintelligencemodelingforgoaldirectedembodiedagents |