Monopoly Deal: A Benchmark Environment for Bounded One-Sided Response
  Games
Card games are widely used to study sequential decision-making under
uncertainty, with real-world analogues in negotiation, finance, and
cybersecurity. These games typically fall into three categories based on the
flow of control: strictly sequential (players alternate single actions),
deterministic response (some actions trigger a fixed outcome), and unbounded
reciprocal response (alternating counterplays are permitted). A less-explored
but strategically rich structure is the bounded one-sided response, where a
player's action briefly transfers control to the opponent, who must satisfy a
fixed condition through one or more moves before the turn resolves. We term
games featuring this mechanism Bounded One-Sided Response Games (BORGs). We
introduce a modified version of Monopoly Deal as a benchmark environment that
isolates this dynamic, where a Rent action forces the opponent to choose
payment assets. The gold-standard algorithm, Counterfactual Regret Minimization
(CFR), converges on effective strategies without novel algorithmic extensions.
A lightweight full-stack research platform unifies the environment, a
parallelized CFR runtime, and a human-playable web interface. The trained CFR
agent and source code are available at https://monopolydeal.ai.
69090e44812eca10f9cc6104
Will Wolf
claimed_verified
2025-11-03T20:50:38.174Z
6522b6330415e1b734e51fee
/avatars/cd2a2b049bc7e4b0f79965e1f54ba25c.svg
William Wolf
cavaunpeu
user
cavaunpeu
Monopoly Deal: A Benchmark Environment for Bounded One-Sided Response
  Games
Card games are widely used to study sequential decision-making under
uncertainty, with real-world analogues in negotiation, finance, and
cybersecurity. These games typically fall into three categories based on the
flow of control: strictly sequential (players alternate single actions),
deterministic response (some actions trigger a fixed outcome), and unbounded
reciprocal response (alternating counterplays are permitted). A less-explored
but strategically rich structure is the bounded one-sided response, where a
player's action briefly transfers control to the opponent, who must satisfy a
fixed condition through one or more moves before the turn resolves. We term
games featuring this mechanism Bounded One-Sided Response Games (BORGs). We
introduce a modified version of Monopoly Deal as a benchmark environment that
isolates this dynamic, where a Rent action forces the opponent to choose
payment assets. The gold-standard algorithm, Counterfactual Regret Minimization
(CFR), converges on effective strategies without novel algorithmic extensions.
A lightweight full-stack research platform unifies the environment, a
parallelized CFR runtime, and a human-playable web interface. The trained CFR
agent and source code are available at https://monopolydeal.ai.
A modified version of Monopoly Deal, featuring Bounded One-Sided Response Games, is used to study sequential decision-making with Counterfactual Regret Minimization.
Counterfactual Regret Minimization CFR Bounded One-Sided Response Games BORGs