// ∞ Algorithms Atlas
Reasoning & Test-Time Compute
Chain of thought, self-consistency, process rewards and test-time scaling behind o1/R1-style reasoners.
8 core1 extended2022–2025
TIMELINE
01Core algorithms
Learn these first. Sorted by year.
Chain-of-Thought Prompting Prompting the model to write intermediate reasoning before answering. 2022core Self-Consistency Samples many reasoning paths and takes the majority answer. 2022core STaR (Self-Taught Reasoner) Bootstraps reasoning by fine-tuning on the model's own correct rationales. 2022core Tree of Thoughts Expands reasoning as a tree searched with self-evaluation and backtracking. 2023core Process Reward Models (PRM) Scores each reasoning step rather than only the final answer. 2023core Self-Refine One model drafts, critiques its own output, then revises – repeated a few times. 2023core Test-Time Compute Scaling Spending more inference compute — thinking, sampling, search — for better answers. 2024core DeepSeek-R1 Reasoning RL Recipe Large-scale outcome-reward RL alone teaches long reasoning and self-reflection. 2025core
02Extended
Variants and follow-ups worth knowing once the core is clear.
03Course units that teach these
U01 Prompting & Using AI Well Prompting techniques: role, context, examples, step-by-step thinking and structured output. 3 h3 algorithms1 papers U52 Reasoning Models: RLVR, GRPO & Test-Time Compute Chain of thought, self-consistency, process rewards, GRPO/DAPO, verifiable rewards and the R1 recipe. 12 h12 algorithms5 papers U82 Agents: Tool Use, MCP, Planning & Memory ReAct, function calling, MCP, reflection, memory, multi-agent systems, computer use and sandboxes. 12 h10 algorithms4 paperslesson ready