• Corpus ID: 238408061

Gambits: Theory and Evidence

@inproceedings{Maharaj2021GambitsTA,
  title={Gambits: Theory and Evidence},
  author={Shivanand Maharaj and Nicholas G. Polson and Christian Turk},
  year={2021}
}
Gambits are central to human decision making. Our goal is to provide a theory of Gambits. A Gambit is a combination of psychological and technical factors designed to disrupt predictable play. Chess provides an environment to study gambits and behavioral economics. Our theory is based on the Bellman optimality path for sequential decision making. This allows us to calculate the Q-values of a Gambit where material (usually a pawn) is sacrificed for dynamic play. On the empirical side, we study… 

Figures and Tables from this paper

References

SHOWING 1-10 OF 38 REFERENCES
Risk-taking in adversarial games: What can 1 billion online chess games tell us?
TLDR
It is found that players not only exhibit state-dependent risk preferences, but also change their risk-taking strategy depending on their opponent, and that this effect differs in experts and novices.
Misbehaving: The Making of Behavioral Economics
Nobel laureate Richard H. Thaler has spent his career studying the radical notion that the central agents in the economy are humans-predictable, error-prone individuals. Misbehaving is his arresting,
Behavioral Game Theory Experiments and Modeling
This chapter reviews recent experimental data testing game theory and behavioral models that have been inspired to explain those data. The models fall into four groups: in cognitive hierarchy or
Analyzing Risky Choices: Q-learning for Deal-No-Deal
In this paper, we derive an optimal strategy for the popular Deal or No Deal game show. To do this, we use Q-learning methods, which quantify the continuation value inherent in sequential decision
Homo Heuristicus: Why Biased Minds Make Better Inferences
TLDR
The study of heuristics shows that less information, computation, and time can in fact improve accuracy, in contrast to the widely held view that less processing reduces accuracy.
Thinking fast and slow.
  • N. McGlynn
  • Medicine, Biology
    Australian veterinary journal
  • 2014
TLDR
Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of the authors' brain’s wiring.
Progress in Behavioral Game Theory
Behavioral game theory aims to predict how people actually behave by incorporating psychological elements and learning into game theory. With this goal in mind, experimental findings can be organized
The role of intuition and deliberative thinking in experts’ superior tactical decision-making
TLDR
This study examines the role of slow deliberation for experts who exhibit superior decision-making outcomes in tactical chess problems with clear best moves and uses advanced computer software to measure the objective value of actions preferred at the start versus the conclusion of decision making.
Mastering the game of Go without human knowledge
TLDR
An algorithm based solely on reinforcement learning is introduced, without human data, guidance or domain knowledge beyond game rules, that achieves superhuman performance, winning 100–0 against the previously published, champion-defeating AlphaGo.
Anomalies: Ultimatums, Dictators and Manners
The recent research on ultimatum and dictator games is reviewed. New experiments reveal that the ultimatum game is quite robust to changes in stakes and the nationality of the players but dictator
...
1
2
3
4
...