Abstract
The ecological psychologist James J. Gibson defined the notion of affordances to refer to what action possibilities environments offer to animals. In this paper, we show how (artificial) agents can discover and exploit affordances in a Multi-Agent System (MAS) environment to achieve their goals. To indicate to agents what affordances are present in their environment and whether it is likely that these may help the agents to achieve their objectives, the environment may expose signifiers while taking into account the current situation of the environment and of the agent. On this basis, we define a Signifier Exposure Mechanism that is used by the environment to compute which signifiers should be exposed to agents in order to permit agents to only perceive information about affordances that are likely to be relevant to them, and thereby increase their interaction efficiency. If this is successful, agents can interact with partially observable environments more efficiently because the signifiers indicate the affordances they can exploit towards given purposes. Signifiers thereby facilitate the exploration and the exploitation of MAS environments. Implementations of signifiers and of the Signifier Exposure Mechanism are presented within the context of a Hypermedia MultiAgent System, and the utility of this approach is presented through the development of a scenario.
| Original language | English |
|---|---|
| Pages (from-to) | 815-835 |
| Number of pages | 21 |
| Journal | Annals of Mathematics and Artificial Intelligence |
| Volume | 92 |
| Issue number | 4 |
| Early online date | 17 Apr 2024 |
| DOIs | |
| Publication status | Published - 1 Aug 2024 |
| Externally published | Yes |
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