Exploring Exploration with Foundation Agents | Danny Sawyer, Research Scientist at Google DeepMind

Danny Sawyer is a Research Scientist at Google DeepMind, investigating agentic exploration in text and embodied environments. He worked on the SIMA 2 project, which introduced a multi-domain instructable agent for open-world video games. Previously, he built biologically inspired vision systems for robots deployed in production at Vicarious. He holds a PhD in Bioengineering from Caltech. In this Frontier Research Club talk, Danny presents Exploring Exploration with Foundation Agents in Interactive Environments, new work on how foundation agents explore when they need to actively gather information instead of receiving everything up front. Paper: https://openreview.net/forum?id=wOrkU... The talk focuses on a core question in agentic AI: can foundation agents explore systematically, or do they mostly rely on undirected trial and error? Danny breaks exploration into three measurable capabilities: efficient information gathering, meta-learning, and strategy adaptation. The work tests these capabilities in controlled zero-shot settings, comparing frontier foundation agents against known optimal policies. The presentation uses two environments. Feature World tests whether agents can efficiently gather information in text-based and 3D settings. Alchemy tests whether agents can learn latent causal rules across trials, adapt when those rules change, and use previous experience to improve future decisions. A key finding is that foundation agents can perform well on simpler information-gathering tasks, but struggle more when exploration requires integrating evidence over time. Simple summarization helps models distill what they have learned, improving meta-learning and adaptation in multi-trial environments. Topics include: • Exploration in foundation agents • Interactive agent evaluation • Zero-shot agent behavior • Efficient information gathering • Meta-learning • Strategy adaptation • Feature World • Text-based environments • 3D embodied environments • Alchemy environment • Latent causal rules • Multi-trial learning • Summarization and reflection • Strategy shifts after rule changes • Comparing agents to optimal policies • Foundation agents in dynamic environments Presented at Frontier Research Club by Danny Sawyer. Recorded on March 18, 2026 at Berkeley Skydeck. Frontier Research Club is a curated forum for rigorous discussion on how AI is reshaping the scientific research process. We convene researchers, computational scientists, and research engineers to examine concrete work across literature synthesis, hypothesis generation, experimental design, simulation, analysis, safety, and reproducibility. Upcoming events: https://luma.com/frontiersyndicate Subscribe for more research talks, technical discussions, and frontier AI presentations.