Behavior control as a function of consciousness. I. World model and goal setting

Osipov, G. S.; Panov, Aleksandr I.; Чудова, Н. В.

doi:10.1134/s1064230714040121

Cited by 27 publications

(4 citation statements)

References 2 publications

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“…It seems that no such systems are presently available. This is a poorly formalized domain, and the present paper seems to be the first in which a constructive goal setting algorithm for anthropocentric objects is described (e.g., see [15]). …”

Section: Discussionmentioning

confidence: 99%

Operational goal setting in anthropocentric objects from the viewpoint of the conceptual model called Etap: I. Structures of algorithms for the support of crew decision-making

Zheltov

Федунов

2015

J. Comput. Syst. Sci. Int.

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From the viewpoint of control of modern complex anthropocentric objects, such objects can be adequately described by the conceptual mathematical model called Etap. This model formal izes both the domain of operation of the anthropocentric objects and the set of tasks to be carried out on the object. Operational goal setting is the first phase of the control of an anthropocentric object. In terms of the Etap model, operational goal setting is the change in the typical situation of the current session of the object operation. The proposed operational goal setting algorithm uses a priori informa tion (a specified sequence of typical situations that ensures the accomplishment of the current session of the object operation, a priori specified set of threats that can emerge in the course of the operation session, a knowledge matrix with the terms of linguistic variables for each pair typical situation-threat) and the current data (obtained from the object's crew and onboard measurement system). For the description of the operational goal setting task, the following concepts are used: the crew circumspec tion, the crew situational awareness, and the crew situational confidence.

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Section: Discussionmentioning

confidence: 99%

Operational goal setting in anthropocentric objects from the viewpoint of the conceptual model called Etap: I. Structures of algorithms for the support of crew decision-making

Zheltov

Федунов

2015

J. Comput. Syst. Sci. Int.

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“…The hierarchy of signs (based on images, significances and personal meanings) serves as a tool for the input signal (low level features) recognition and for the corresponding sign actualization. An algorithm of sign recognition is simple comparison of input features with corresponding set of features predicted by upper level signal on each level of the hierarchy [25]. In this way the recognition process is bottom-up spreading of the activation in the hierarchy of features right down to levels where there is correspondence between features and signs.…”

Section: Knowledge Representationmentioning

confidence: 99%

“…These representations and planners based on them should solve symbol grounding problem [24] and support goal-setting and role distribution procedures. Such requirements can be met by the sign representation, which is based on the models of cognitive functions [25] and neurophysiological studies of the cognition process [27,26]. We will use this approach to realize communication protocol for cooperative planning and providing a link between the symbolic models and sensor (low level) data.…”

Section: Introductionmentioning

confidence: 99%

Behavior and Path Planning for the Coalition of Cognitive Robots in Smart Relocation Tasks

Panov¹,

Yakovlev²

2016

Advances in Intelligent Systems and Computing

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Abstract. In this paper we outline the approach of solving special type of navigation tasks for robotic systems, when a coalition of robots (agents) acts in the 2D environment, which can be modified by the actions, and share the same goal location. The latter is originally unreachable for some members of the coalition, but the common task still can be accomplished as the agents can assist each other (e.g. by modifying the environment). We call such tasks smart relocation tasks (as the can not be solved by pure path planning methods) and study spatial and behavior interaction of robots while solving them. We use cognitive approach and introduce semiotic knowledge representation -sign world model which underlines behavioral planning methodology. Planning is viewed as a recursive search process in the hierarchical state-space induced by sings with path planning signs reside on the lowest level. Reaching this level triggers path planning which is accomplished by state of the art grid-based planners focused on producing smooth paths (e.g. LIAN) and thus indirectly guarantying feasibility of that paths against agent's dynamic constraints.

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“…We use knowledge representation framework proposed in [16,17] for world model description. Within this framework the grounded symbol [7] is defined by the four component structure entitled a sign -name, image, significance and personal meaning.…”

Section: Introductionmentioning

confidence: 99%

Psychologically Inspired Planning Method for Smart Relocation Task

Panov

Yakovlev

2016

Procedia Computer Science

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Behavior planning is known to be one of the basic cognitive functions, which is essential for any cognitive architecture of any control system used in robotics. At the same time most of the widespread planning algorithms employed in those systems are developed using only approaches and models of Artificial Intelligence and don't take into account numerous results of cognitive experiments. As a result, there is a strong need for novel methods of behavior planning suitable for modern cognitive architectures aimed at robot control. One such method is presented in this work and is studied within a special class of navigation task called smart relocation task. The method is based on the hierarchical two-level model of abstraction and knowledge representation, e.g. symbolic and subsymbolic. On the symbolic level sign world model is used for knowledge representation and hierarchical planning algorithm, MAP, is utilized for planning. On the subsymbolic level the task of path planning is considered and solved as a graph search problem. Interaction between both planners is examined and inter-level interfaces and feedback loops are described. Preliminary experimental results are presented.

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Behavior control as a function of consciousness. I. World model and goal setting

Cited by 27 publications

References 2 publications

Operational goal setting in anthropocentric objects from the viewpoint of the conceptual model called Etap: I. Structures of algorithms for the support of crew decision-making

Operational goal setting in anthropocentric objects from the viewpoint of the conceptual model called Etap: I. Structures of algorithms for the support of crew decision-making

Behavior and Path Planning for the Coalition of Cognitive Robots in Smart Relocation Tasks

Psychologically Inspired Planning Method for Smart Relocation Task

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