Markov Chains for the RISK Board Game Revisited
نویسنده
چکیده
Probabilistic reasoning goes a long way in many popular board games. Abbott and Richey [1] and Ash and Bishop [2] identify the most profitable properties in Monopoly and Tan [3] derives battle strategies for RISK. In RISK, the stochastic progress of a battle between two players over any of the 42 countries can be described using a Markov Chain. Theory for Markov Chains can be applied to address questions about the probabilities of victory and expected losses in battle.
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