Strategic reasoning

Analyses of eye movements are challenging because one has to deal with great variability typically found in eye movement data. There have been extensive formal debates about the merits of the principle of backward induction among game theorists and logicians. Experience with world-physics allows players to see easily how the marble will run through a game, and which player can change the path of the white marble at each decision point. It is basically the plan of action an agent or a group of agents considers for its interactions, that can be modelled as games. To test what strategies participants may have used, we construct computational cognitive models cf. As described in Sect. However, for the sake of uniform presentation, we do not distinguish between leaf nodes and non-leaf nodes as far as player labelling is concerned. In the games they designed, the path of a white marble can be manipulated by removing trapdoors Fig. They need to apply second-order reasoning, that is, they need to reason about what the computer, at the second set of trapdoors, thinks that they, at the third set of trapdoors, think. The participants successfully applied second-order social reasoning in a great proportion i. Strategy is one of the basic ingredients of multi-agent interaction. Earlier, Hedden and Zhang and Flobbe et al.

It can be used as a rule in the future if a generic applicability condition can be stated. The paper presents a formal language to represent different strategies on a finer-grained level than was possible before.

strategic reasoning definition

The proportions are depicted separately for games in which Player I should stop Fig. As sketched above, the game-theoretic perspective assumes that people are rational agents, optimizing their gain by applying strategic reasoning.

We consider the notion of partial strategies formalised below as a way to model such resource-bounded strategic reasoning. In strategic reasoning, one does not expect to have hard and fast conclusions that have guaranteed outcomes in contrast to conventional logical inferencenor to have qualitatively optimized solutions.

Strategic reasoning

Meijering et al. The past moves and reasoning of the players are not taken into consideration. This allowed Johnson and colleagues to record what the participants select at a particular time within the reasoning process.

In this article, an extension of Ghosh et al. We provide below an explicit description of the backward induction algorithm in extensive form game trees Jones In contrast, backward induction would yield a higher proportion of first fixations on bins 3 and 4, as backward reasoning starts with comparing payoffs in bins 3 and 4. The eye movements and fixations on payoffs provide some insight in the strategies that participants used. Initially all nodes are unlabelled. It can be used as a rule in the future if a generic applicability condition can be stated. In their sequential bargaining experiment, participants had to bargain with one other player. A white marble is about to drop, and its path can be manipulated by removing trapdoors i. We briefly explain the experiment and its results below. In this example, the participant controls the blue trapdoors and the computer controls the orange ones.

The findings of this experiment, together with behavioral results, help to determine the cognitive bounds on higher-order social reasoning in a dynamic game. For each player, the goal is that the white marble drops into the bin that contains the darkest possible color-graded marble of their color.

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Strategic Reasoning