Add bidding-based discussion turn-taking - #20
Merged
Conversation
Competitive research turned up Google's Werewolf Arena, whose key idea is a
dynamic turn order where agents bid to speak rather than following fixed
seating. deepwolf now supports the same — with a twist.
- GameConfig gains a validated `discussion_mode` ("ordered" default, or
"bidding"); a --bidding CLI flag on simulate and play.
- engine.py: _speaking_order collects a bid from every living agent, emits each
bid as a public SPEAK_BID event, and seats speakers highest-bid-first.
- deepwolf's innovation over Werewolf Arena: bids are public (priority + a
reason), so an eager bid with a thin reason is a signal other agents and the
copilot can read — consistent with the project's "everything explainable".
- agents: new concrete Agent.bid; RandomAgent, LLMAgent and HumanAgent override
it. Bilingual strings; the mock handles the new decision kind.
- 7 new tests. English/ordered output is unchanged.
Closes #19
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Code review (post-merge record).
Clean increment. Merged via squash. |
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Summary
Implements #19 — bidding-based discussion turn-taking, the highest-value item
from this cycle's competitive research.
Research that motivated it
Google's Werewolf Arena (arXiv:2407.13943) introduced a dynamic turn order
where agents bid to speak instead of following a fixed seating order — it
better mirrors real discussion. deepwolf used fixed seating order; every serious
comparable project has moved past that.
What this adds
GameConfig.discussion_mode— validated,"ordered"(default) or"bidding";a
--biddingflag onsimulateandplay.engine._speaking_order()collects a bid from each living agent, emits eachas a public
SPEAK_BIDevent, and seats speakers highest-bid-first (ties byseat).
Agent.bid()— new concrete method;RandomAgent,LLMAgentand the CLIHumanAgentoverride it. Bilingual prompts; the offline mock handles the newbiddecision kind.deepwolf's innovation over the original
Werewolf Arena's bids are an internal mechanism. Here bids are public — a
priority and a reason, emitted as events. An eager bid backed by a thin reason
is itself a tell that other agents and the copilot can read. That fits
deepwolf's "everything is explainable" principle.
Checklist
ruff/mypy/pytest(67 tests, 7 new) all pass"ordered"— existing games and English output unchangedCloses #19