Abstract
For an autonomous physical agent, such as a moving robot or a person with their mobile device, performing a task in a spatio-temporal environment often requires interaction with other agents. In this paper we study ad-hoc collaborative planning between these autonomous peers. We introduce the notion of decentralized time geography, which differs from the traditional time-geographic framework by taking into account limited local knowledge. This allows agents to perform a space-time analysis within a time-geographic framework that represents local knowledge in a distributed environment as required for ad-hoc coordinated action between agents in physical space. More specifically, we investigate the impact of general agent movement, replacement seeking, and location and goal-directed behavior of the initiating agent on the outcome of the collaborative planning. Empirical tests in a multi-agent simulation framework provide both a proof of concept and specific results for different combinations of agent density and communication radius.
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Raubal, M., Winter, S., Dorr, C. (2009). Decentralized Time Geography for Ad-Hoc Collaborative Planning. In: Hornsby, K.S., Claramunt, C., Denis, M., Ligozat, G. (eds) Spatial Information Theory. COSIT 2009. Lecture Notes in Computer Science, vol 5756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03832-7_27
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DOI: https://doi.org/10.1007/978-3-642-03832-7_27
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