Notes on "Patterns and problems in emerging multiagent systems"

Part two of my notes series, with hopefully many more to come. Comments are much appreciated. Article: https://www.anthropic.com/research/multiagent-systems -------------------- Paper summary (What) Institutions are designed for people, but soon, we'll have far more agents interacting in the real world. Agent-to-agent interactions could become the most common form of interaction before we understand how to make them go well. Tendencies from individual agents can snowball into larger issues. To examine how inter-agent actions can work in the real world, Anthropic carried out a variety of tests. Issues addressed by the paper (Why) Agents seem to currently work like humans with early chatbots. They can easily spin up subagents (e.g. humans opening new chatbot tabs) and work efficiently, but don't treat other agents like peers with their own goals, and have no clean hierarchy. Essentially, they don't seem to be able to carry out the same interpersonal actions we can. Highly parallelizable tasks seem to be far easier for multiagent systems. Detailed Information (How) Coordination vs Parallelization Anthropic essentially tosses 45 agents into a box, gives them a forum to communicate, and identical instructions to find vulnerabilities in 15 open-source software projects and review each other's findings. Then, an arbiter agent is instantiated to make final decisions on whether suggestions from the agent team are "new and valid." I'm not a huge fan of this graph, but to summarize, both Mythos Preview and Opus 4.8 were tested: MP found 266 vulnerabilities, and Opus found 41 vulnerabilities. In contrast, their parallelized versions only found 21 and 14 vulnerabilities, respectively. They found 12 and 3 vulnerabilities in common, respectively. At first glance, the coordinated approach seems far better, but the coordinated swarms also used far more tokens and half of their discoveries (for Mythos) were outside of the directories in which the independent agents were told to search. When comparing only core directories, the two approaches seem to be around even in terms of tokens/vulnerability. As mentioned in the article, it seems from the low number of vulnerabilities in common that these two methods are complementary, and their approaches were quite different. The coordinated group focused on where vulnerabilities might be easiest to find, built their own tools, and learned to specialize, while the parallelized group were preassigned to search specific areas in a repo. Anthropic Prediction: "In the future, we predict that this sort of specialization and coordination will dominate over uncoordinated brute-force search." My prediction: Honestly, I'm quite in line with Anthropic on this one, though I do think there's some merit in continuing to just use both methods simultaneously until the vulnerabilities in common rise significantly. Also, the coordinated group didn't really depend on each other, so they weren't held up by each other's work, and when they did rely on each other, coordination got much more difficult. As mentioned, this would be important in large-scale SWE projects. Coordination Testing To test this, Anthropic had different coordinated swarms attempt to make a text-based fantasy game. Not going to go into the specifics of initialization, but 3 different prompts were used. The first gave the most autonomy and told them to form teams and work together, the second gave ideas of which teams to form (programming, art, playtesting, etc.), and the third made one agent the CEO (all other agents take instructions from the CEO). Resulting games from all three prompt variants were trash "predictably bad". Newer models seem to close and merge more of their open PRs. Only Sonnet 5 seems to do this while sharing code well. I don't think the definition of code sharing in the article is very clear, so here's my interpretation. Also since they didn't include the math I had to make it up myself. If there are any brave commenters please tell me if this paragraph is intentionally confusing or if I'm just dumb: Code sharing (agent-file pair) - proportion of a file written by other agents, relative to the agent in consideration Code sharing (agent) - Weighted avg of the agent's file-level code sharing across all files Weighted by proportion of code on each file the agent wrote itself Hopefully you all can read my handwriting. If you can't then blame Anthropic for not giving out the math themselves. Anyway, this is all to say that super tiny edits don't make an agent look collaborative. This is why basically every model other than Sonnet 5 looks kinda bad. Sonnet/Opus 4.6 worked together, but coordination was poor and PRs conflicted and were left unmerged. On the other hand, Opus 4.8 and Mythos largely avoided the problem by simply working on their own files. Behavior and Failures Another issue was that individual agents were too similar. They would generally take the same actions in the same situations, whereas different