Pages that link to "Item:Q2384141"
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The following pages link to AWESOME: a general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents (Q2384141):
Displaying 16 items.
- AWESOME (Q55828) (← links)
- Belief and truth in hypothesised behaviours (Q274416) (← links)
- Making friends on the fly: cooperating with new teammates (Q343919) (← links)
- On the rate of convergence of fictitious play (Q372994) (← links)
- Learning to compete, coordinate, and cooperate in repeated games using reinforcement learning (Q413845) (← links)
- Perspectives on multiagent learning (Q1028921) (← links)
- A hierarchy of prescriptive goals for multiagent learning (Q1028932) (← links)
- Conjectural equilibrium in multiagent learning (Q1277049) (← links)
- Colearning in differential games (Q1277050) (← links)
- Autonomous agents modelling other agents: a comprehensive survey and open problems (Q1639697) (← links)
- Negotiating team formation using deep reinforcement learning (Q2046007) (← links)
- Multi-agent reinforcement learning: a selective overview of theories and algorithms (Q2094040) (← links)
- A distributed algorithm to obtain repeated games equilibria with discounting (Q2284815) (← links)
- A general criterion and an algorithmic framework for learning in multi-agent systems (Q2384145) (← links)
- On the Rate of Convergence of Fictitious Play (Q3162511) (← links)
- Evaluation and learning in two-player symmetric games via best and better responses (Q6095620) (← links)
