HLSMAC: A New StarCraft Multi-Agent Challenge for High-Level Strategic Decision-Making
AAMAS'26, 2026. [All Versions]. Benchmarks are crucial for assessing multi-agent reinforcement learning (MARL) algorithms. While StarCraft II-related environments have driven significant advances in MARL, existing benchmarks like SMAC focus primarily on micromanagement…
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JARVIS-1: Open-World Multi-Task Agents With Memory-Augmented Multimodal Language Models ieeexplore.ieee.org
IEEE Transactions on Pattern Analysis and Machine Intelligence. [All Versions]. Achieving human-like planning and control with multimodal observations in an open world is a key milestone for more functional generalist agents. Existing approaches can handle certain long-horizon…
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ai-evaluation github.com
Open-source LLM and agent evaluation framework with 50+ metrics, LLM-as-Judge augmentation, and guardrail scanners (jailbreak, PII, prompt-injection). Useful for scoring RAG outputs, agent trajectories, and function-calling behavior in data-science workflows.
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AGENT: A Benchmark for Core Psychological Reasoning proceedings.mlr.press
ICML'21, 2021. [All Versions]. Inspired by cognitive development studies on intuitive psychology, this paper presents a benchmark consisting of a large dataset of procedurally generated 3D animations, AGENT (Action, Goal, Efficiency, coNstraint, uTility), structured around four…
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AGI & CoCoSci › Papers > Communications > Coordination: “AAMAS'26, 2026. [All Versions]. Benchmarks are crucial for assessing multi-agent reinforcement learning (MARL) algorithms. While StarCraft II-related environments have driven significant advances in MARL, existing benchmarks like SMAC focus primarily on micromanagement…”