Phu Sakulwongtana

collaborators

2 papers

cs.MA2019

$α^{α}$ -Rank: Practically Scaling $α$ -Rank through Stochastic Optimisation

Yaodong Yang, Rasul Tutunov, Phu Sakulwongtana +1

Recently, $α$ -Rank, a graph-based algorithm, has been proposed as a solution to ranking joint policy profiles in large scale multi-agent systems. $α$ -Rank claimed tractability thro…

cs.GT2019

Infer Your Enemies and Know Yourself, Learning in Real-Time Bidding with Partially Observable Opponents

Manxing Du, Alexander I. Cowen-Rivers, Ying Wen +4

Real-time bidding, as one of the most popular mechanisms for selling online ad slots, facilitates advertisers to reach their potential customers. The goal of bidding optimization i…

αα-Rank: Practically Scaling α-Rank through Stochastic Optimisation

Infer Your Enemies and Know Yourself, Learning in Real-Time Bidding with Partially Observable Opponents

$α^{α}$ -Rank: Practically Scaling $α$ -Rank through Stochastic Optimisation