Can rats solve a simple version of the traveling salesman problem?

Bureš, Jan; Burešová, O.; Nerad, Luděk

doi:10.1016/s0166-4328(05)80223-2

Cited by 33 publications

(23 citation statements)

References 26 publications

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“…In Experiment 1 we demonstrated that participants outperformed the simple NN strategy, that has been suggested to be involved in human and animal path planning (e.g., Gärling & Gärling, 1988;Bures, Buresova, & Nerad, 1992). This result demonstrates that the NN-strategy is not suYcient to explain planning behavior for complex TSPs.…”

Section: Resultsmentioning

confidence: 79%

Planning paths to multiple targets: memory involvement and planning heuristics in spatial problem solving

Wiener

Ehbauer

Mallot

2008

Psychological Research

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For large numbers of targets, path planning is a complex and computationally expensive task. Humans, however, usually solve such tasks quickly and efficiently. We present experiments studying human path planning performance and the cognitive processes and heuristics involved. Twenty-five places were arranged on a regular grid in a large room. Participants were repeatedly asked to solve traveling salesman problems (TSP), i.e., to find the shortest closed loop connecting a start location with multiple target locations. In Experiment 1, we tested whether humans employed the nearest neighbor (NN) strategy when solving the TSP. Results showed that subjects outperform the NN-strategy, suggesting that it is not sufficient to explain human route planning behavior. As a second possible strategy we tested a hierarchical planning heuristic in Experiment 2, demonstrating that participants first plan a coarse route on the region level that is refined during navigation. To test for the relevance of spatial working memory (SWM) and spatial long-term memory (LTM) for planning performance and the planning heuristics applied, we varied the memory demands between conditions in Experiment 2. In one condition the target locations were directly marked, such that no memory was required; a second condition required participants to memorize the target locations during path planning (SWM); in a third condition, additionally, the locations of targets had to retrieved from LTM (SWM and LTM). Results showed that navigation performance decreased with increasing memory demands while the dependence on the hierarchical planning heuristic increased.

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Section: Resultsmentioning

confidence: 79%

Planning paths to multiple targets: memory involvement and planning heuristics in spatial problem solving

Wiener

Ehbauer

Mallot

2008

Psychological Research

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“…As pointed out in the introduction, not all spatial planning strategies described in the literature allow deriving predictions in the present scenario. Hence, we concentrate on the following planning strategies: First, the NN strategy, predicting that the closest target place is repeatedly chosen until all targets have been visited (Bureš et al, 1992;Gärling & Gärling, 1988;Gärling et al, 1986); and second, hierarchical planning strategies that can, in principle, be applied to the present scenario-the cluster strategy (Gallistel & Cramer, 1996;Wiener et al, 2004), the hNN method (Vickers, Bovet, et al, 2003), and the region-based planning strategy (Wiener & Mallot, 2003). All three hierarchical strategies have this in common: that the environment is structured into the different clusters or regions taken into account during planning.…”

Section: Methodsmentioning

confidence: 99%

Path planning under spatial uncertainty

2008

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“…The computation ofa path even between multiple goals is implicit in the generation of expectation values. This readout mechanism can provide a solution to the traveling salesman problem of finding a short path between multiple destinations (see Bures, Buresova, &Nerad, 1992, andGallistel, 1997, for studies in rats and monkeys, respectively) without ever retrieving any coordinates or explicitly computing distances.…”

Section: Some Ways Of Reading Out the Goal Locationmentioning

confidence: 99%

Possible uses of path integration in animal navigation

Biegler

2000

Animal Learning & Behavior

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Can rats solve a simple version of the traveling salesman problem?

Cited by 33 publications

References 26 publications

Planning paths to multiple targets: memory involvement and planning heuristics in spatial problem solving

Planning paths to multiple targets: memory involvement and planning heuristics in spatial problem solving

Path planning under spatial uncertainty

Possible uses of path integration in animal navigation

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