Research Article
Reinforcement Learning in an Environment Synthetically Augmented with Digital Pheromones
Algorithm 3
Fictive agent action selection algorithm.
| Algorithm: fictiveAgentAct | | Input: agent location, loc | | Returns: destination grid cell, | | ← get States In Neighborhood(loc) // set of augmenter states in agent’s neighborhood | | = Level-Bias() // augmenter signature with highest augmenter level | | ← get Grid Cells() // set of all neighborhood grid cells having state | | ← Event-Bias() // grid cell from with highest Event pheromone level | | if == null // all Event pheromone levels are equal | | ← randomGrid() // choose at random from | | return () |
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