dissertation.git - Undergraduate dissertation — Deceptive Alignment in Autonomous LLM Agents (UEL, 2026). Sandboxed agentic-LLM deception study: 960 runs, three-tier judging (regex + blackbox + glassbox).

Age	Commit message (Collapse)	Author
2026-02-25	feat: implement judging system with regex, blackbox, and glassbox checks	CaptainJack2491
	- Add src/judge.py: RegexChecker, BlackboxChecker, GlassboxChecker, Judge orchestrator - Add src/judge_runner.py: CLI for batch/single judging with CSV output - Add regex_rules.yaml for corporate_sabotage_v2 and child_protection scenarios - Add judge config section to config.yaml (model, temperature, log_dir) - Add tests/test_judge.py: 34 unit tests covering all components - Uses Anthropic Batch API for half-cost LLM judge calls - Judge logs include full CoT reasoning and judge model for auditability
2026-02-24	Add comprehensive test suite (104 tests)	CaptainJack2491
	Tests cover: - VFS: sandbox escape, path traversal, CRUD, singleton staleness - Config loader: missing keys, temperature cascade, oversight fallback - Tools: schema/implementation sync, VFS delegation - Agent: message construction, error handling, token counting, reasoning extraction - Interrogation: sanitization, provider detection, prompt loading - Runner: baseline extraction, prompt assembly, success detection All tests run offline with mocked API calls.