Every system this module studies โ a thermostat, a chess program, a warehouse robot, a large language model calling tools on its own behalf โ shares one property: it sits inside an environment, takes in informationโฆ
The foundational cognitive cycle page set out a full model: ten components, densely cross-connected, more than most real systems ever need. This page asks a more practical question โ starting from almost nothing andโฆ
Before you build an agent, you need to specify what it actually is โ and it turns out two entirely separate disciplines, working on entirely separate problems, converged on the same first move: force the specificationโฆ
The cognitive cycle names Think as a distinct stage without saying how it's actually implemented. Here we look at the two fundamentally different answers computer science has produced, using two real, contrastingโฆ
Polyglot Programming & Paradigm Shifting draws the line between logic programming and goal-oriented programming precisely: one answers "is this true?", the other answers "what sequence of actions gets me from here to aโฆ
Every page in this module so far has treated an agent as a single thing reasoning about a world. Almost every real deployment involves more than one. Let's take a look at how separate agents actually exchangeโฆ
Every capability this module has covered comes with a corresponding failure mode, and the failure modes are worth studying as carefully as the capabilities, because they don't announce themselves. A brittle agent, aโฆ
When Agents Fail: Brittleness, Misaligned Incentives, and Deception named three ways an agent fails without announcing it. Here we look at concrete design responses โ not a way to make these failures impossible, sinceโฆ
A personal knowledge tool that acquired several of the functions a cognitive architecture needs, and what that does and does not show
The multi-agent systems page covers several mechanisms agents use to exchange information, from direct signals to shared resources to formal communication languages. This page asks a narrower question about all of themโฆ
This site's material on AI Ethics covers bias, fairness, and the regulatory landscape for AI systems broadly. This page narrows the focus to a problem specific to autonomous action rather than classification orโฆ