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Agent development as a strategy shaper

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Abstract

This paper studies to what extent agent development changes one’s own strategy. While this question has many general implications it is of special interest to the study of peer designed agents (PDAs), which are computer agents developed by non-experts. This latter emerging technology, has been widely advocated in recent literature for the purpose of replacing people in simulations and investigating human behavior. Its main premise is that strategies programmed into these agents reliably reflect, to some extent, the behavior used by their programmers in real life. We show that PDA development has an important side effect that has not been addressed to date—the process that merely attempts to capture one’s strategy is also likely to affect the developer’s strategy. This result has many implications concerning the appropriate design of PDA-based simulations as well as the validity of using PDAs for studying individual decision making. The phenomenon is demonstrated experimentally, using two very different application domains and several performance measures. Our findings suggest that the effects on one’s strategy arise both in situations where it is potentially possible for people to reason about the optimal strategy (in which case PDA development will enhance the use of an optimal strategy) and in those where calculating the optimal strategy is computationally challenging (in which case PDA development will push people to use more effective strategies, on average). Since in our experiments PDA development actually improved the developer’s strategy, PDA development can be suggested as a means for improving people’s problem solving skills. Finally, we show that the improvement achieved in people’s strategies through agent development is not attributed to the expressive aspect of agent development per-se but rather there is a crucial additional gain in the process of designing and programming ones strategy into an agent.

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Notes

  1. The inefficiency improvement measures the decrease (in percentages) in the difference between the average result achieved and the theoretical bound (6 in the case of outcome performance), as the difference between the two represents the strategy’s inefficiency.

  2. This kind of analysis for the outcome performance measure is futile, since this measure, when taken individually, highly depends on chance.

  3. The idea was to equalize conditions, so that people would have the chance to thoroughly think through their stated strategy, much like how PDA development takes some time. people will have the chance to thoroughly think through their stated strategy.

  4. For a comparison between AMT and other recruitment methods see [14].

  5. Note that better performance of the adversary (the human players) infers worse performance of the patrolling strategy.

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Acknowledgments

We would like to thank Amos Azaria for helping us to collect the data for the no-PDA experiment. A preliminary version of this paper was presented at HAIDM14, and appears in the proceedings of AAAI 2014 [46] and AAMAS 2014 [47].

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Authors and Affiliations

  1. Department of Computer Science, Bar-Ilan University, Ramat Gan, Israel

    Avshalom Elmalech, David Sarne & Noa Agmon

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  1. Avshalom Elmalech
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Correspondence to Avshalom Elmalech.

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Elmalech, A., Sarne, D. & Agmon, N. Agent development as a strategy shaper. Auton Agent Multi-Agent Syst 30, 506–525 (2016). https://doi.org/10.1007/s10458-015-9299-z

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