activity
20162024
most citedImproved Image Captioning via Policy Gradient optimization of SPIDEr

452 citations · 907 across the 16 of their papers we have counts for

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8 papers · 1 filter

cs.AI2024

Neural Population Learning beyond Symmetric Zero-sum Games

Siqi Liu, Luke Marris, Marc Lanctot +3

We study computationally efficient methods for finding equilibria in n-player general-sum games, specifically ones that afford complex visuomotor skills. We show how existing metho…

cs.AI2022★ 1 cited

Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games

Siqi Liu, Marc Lanctot, Luke Marris +1

Learning to play optimally against any mixture over a diverse set of strategies is of important practical interests in competitive games. In this paper, we propose simplex-NeuPL th…

cs.AI2022★ 1 cited

NeuPL: Neural Population Learning

Siqi Liu, Luke Marris, Daniel Hennes +3

Learning in strategy games (e.g. StarCraft, poker) requires the discovery of diverse policies. This is often achieved by iteratively training new policies against existing ones, gr…

cs.AI2021

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity

Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu +5

Strategic diversity is often essential in games: in multi-player games, for example, evaluating a player against a diverse set of strategies will yield a more accurate estimate of…

cs.AI2021★ 12 cited

From Motor Control to Team Play in Simulated Humanoid Football

Siqi Liu, Guy Lever, Zhe Wang +19

Intelligent behaviour in the physical world exhibits structure at multiple spatial and temporal scales. Although movements are ultimately executed at the level of instantaneous mus…

cs.AI2019★ 39 cited

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg +11

Some of the most successful applications of deep reinforcement learning to challenging domains in discrete and continuous control have used policy gradient methods in the on-policy…

cs.AI2019★ 81 cited

Emergent Coordination Through Competition

Siqi Liu, Guy Lever, Josh Merel +3

We study the emergence of cooperative behaviors in reinforcement learning agents by introducing a challenging competitive multi-agent soccer environment with continuous simulated p…

cs.AI2018★ 68 cited

Hierarchical visuomotor control of humanoids

Josh Merel, Arun Ahuja, Vu Pham +5

We aim to build complex humanoid agents that integrate perception, motor control, and memory. In this work, we partly factor this problem into low-level motor control from proprioc…