Determining action selection policies of an execution device

A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:

• identifying a plurality of possible actions in a state, wherein the state corresponds to a vector of information sets, and each information set in the vector of information sets comprises a sequence of actions taken by an execution device that leads to the state;
• identifying a vector of current action selection policies in the state, wherein each current action selection policy in the vector of current action selection policies corresponds to an information set in the vector of information sets, and an action selection policy specifies a respective probability of selecting an action among the plurality of possible actions in the state;
• computing a sampling policy based on the vector of current action selection policies in the state, wherein the sampling policy specifies a respective sampling probability corresponding to each of the plurality of possible actions in the state;
• sampling an action among the plurality of possible actions in the state according to a sampling probability of the action specified in the sampling policy;
• and
• updating the each current action selection policy in the vector of current action selection policies of the execution device in the state based on the action.

A computer-implemented system, comprising:

• one or more computers;
• and
• one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations comprising:
• identifying a plurality of possible actions in a state, wherein the state corresponds to a vector of information sets, and each information set in the vector of information sets comprises a sequence of actions taken by an execution device that leads to the state;
• identifying a vector of current action selection policies in the state, wherein each current action selection policy in the vector of current action selection policies corresponds to an information set in the vector of information sets, and an action selection policy specifies a respective probability of selecting an action among the plurality of possible actions in the state;
• computing a sampling policy based on the vector of current action selection policies in the state, wherein the sampling policy specifies a respective sampling probability corresponding to each of the plurality of possible actions in the state;
• sampling an action among the plurality of possible actions in the state according to a sampling probability of the action specified in the sampling policy;
• and
• updating the each current action selection policy in the vector of current action selection policies of the execution device in the state based on the action.