682 citations · 1.1k across the 12 of their papers we have counts for
13 papers
A Theory of Appropriateness That Accounts for Norms of Rationality
Joel Z. Leibo, Alexander Sasha Vezhnevets, Manfred Diaz +10
We propose a society-first theory of normative appropriateness where individuals, modeled as pre-trained actors with cognitive architectures analogous to Large Language Models (LLM…
SIMA 2: A Generalist Embodied Agent for Virtual Worlds
SIMA team, Adrian Bolton, Alexander Lerchner +63
We introduce SIMA 2, a generalist embodied agent that understands and acts in a wide variety of 3D virtual worlds. Built upon a Gemini foundation model, SIMA 2 represents a signifi…
Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia
Chandler Smith, Marwa Abdulhai, Manfred Diaz +83
Large Language Model (LLM) agents have demonstrated impressive capabilities for social interaction and are increasingly being deployed in situations where they might engage with bo…
A theory of appropriateness with applications to generative artificial intelligence
Joel Z. Leibo, Alexander Sasha Vezhnevets, Manfred Diaz +11
What is appropriateness? Humans navigate a multi-scale mosaic of interlocking notions of what is appropriate for different situations. We act one way with our friends, another with…
Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia
Alexander Sasha Vezhnevets, John P. Agapiou, Avia Aharon +7
Agent-based modeling has been around for decades, and applied widely across the social and natural sciences. The scope of this research method is now poised to grow dramatically as…
Heterogeneous Social Value Orientation Leads to Meaningful Diversity in Sequential Social Dilemmas
Udari Madhushani, Kevin R. McKee, John P. Agapiou +6
In social psychology, Social Value Orientation (SVO) describes an individual's propensity to allocate resources between themself and others. In reinforcement learning, SVO has been…
Melting Pot 2.0
John P. Agapiou, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán +14
Multi-agent artificial intelligence research promises a path to develop intelligent technologies that are more human-like and more human-compatible than those produced by "solipsis…
Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria
Kavya Kopparapu, Edgar A. Duéñez-Guzmán, Jayd Matyas +7
A key challenge in the study of multiagent cooperation is the need for individual agents not only to cooperate effectively, but to decide with whom to cooperate. This is particular…
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Joel Z. Leibo, Edgar Duéñez-Guzmán, Alexander Sasha Vezhnevets +7
Existing evaluation suites for multi-agent reinforcement learning (MARL) do not assess generalization to novel situations as their primary objective (unlike supervised-learning ben…
A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings
Eugene Vinitsky, Raphael Köster, John P. Agapiou +3
Society is characterized by the presence of a variety of social norms: collective patterns of sanctioning that can prevent miscoordination and free-riding. Inspired by this, we aim…
StarCraft II: A New Challenge for Reinforcement Learning
Oriol Vinyals, Timo Ewalds, Sergey Bartunov +22
This paper introduces SC2LE (StarCraft II Learning Environment), a reinforcement learning environment based on the StarCraft II game. This domain poses a new grand challenge for re…
Deep Q-learning from Demonstrations
Todd Hester, Matej Vecerik, Olivier Pietquin +11
Deep reinforcement learning (RL) has achieved several high profile successes in difficult decision-making problems. However, these algorithms typically require a huge amount of dat…
Strategic Attentive Writer for Learning Macro-Actions
Alexander, Vezhnevets, Volodymyr Mnih +5
We present a novel deep recurrent neural network architecture that learns to build implicit plans in an end-to-end manner by purely interacting with an environment in reinforcement…