Chemotaxis emerges as the optimal solution to cooperative search games
| Autor: | Alberto Pezzotta, Antonio Celani, Matteo Adorisio |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Mathematical optimization Forgetting Computer science Control (management) FOS: Physical sciences Analogy Chemotaxis 02 engineering and technology Motion (physics) 03 medical and health sciences 030104 developmental biology Energy expenditure Biological Physics (physics.bio-ph) Search algorithm 0202 electrical engineering electronic engineering information engineering Production (economics) 020201 artificial intelligence & image processing Physics - Biological Physics |
| Zdroj: | Physical Review E. 98 |
| ISSN: | 2470-0053 2470-0045 |
| Popis: | Cooperative search games are collective tasks where all agents share the same goal of reaching a target in the shortest time while limiting energy expenditure and avoiding collisions. Here we show that the equations that characterize the optimal strategy are identical to a long-known phenomenological model of chemotaxis, the directed motion of microorganisms guided by chemical cues. Within this analogy, the substance to which searchers respond acts as the memory over which agents share information about the environment. The actions of writing, erasing, and forgetting are equivalent to production, consumption, and degradation of chemoattractant. The rates at which these biochemical processes take place are tightly related to the parameters that characterize the decision-making problem, such as learning rate, costs for time, control, collisions and their tradeoffs, as well as the attitude of agents toward risk. We establish a dictionary that maps notions from decision-making theory to biophysical observables in chemotaxis, and vice versa. Our results offer a fundamental explanation of why search algorithms that mimic microbial chemotaxis can be very effective and suggest how to optimize their performance. |
| Databáze: | OpenAIRE |
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