pith. machine review for the scientific record. sign in

arxiv: 2604.27917 · v1 · submitted 2026-04-30 · 💻 cs.LO · math.LO

Recognition: unknown

A Logic of Inability

Authors on Pith no claims yet

Pith reviewed 2026-05-07 05:33 UTC · model grok-4.3

classification 💻 cs.LO math.LO
keywords coalition logicinability operatormulti-agent systemsmodal logicconservative extensionagencyimpossibilitynegation
0
0 comments X

The pith

Coalition Logic gains an explicit inability operator by defining it as the negation of ability, creating a conservative extension with its own modal laws.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper adds an operator for what coalitions cannot achieve to Coalition Logic, treating it simply as the logical opposite of what they can achieve. This produces a sound, complete, and conservative extension, so all prior theorems about ability remain unchanged while new facts about limits become provable. The operator displays anti-monotonicity in coalition size, contravariance in goal strength, asymmetric behavior under conjunction and disjunction, failure of superadditivity, non-equivalence to opponent ability, and a link between grand-coalition inability and overall systemic impossibility. These properties matter in safety-critical multi-agent systems where designers must specify not only permitted actions but also outcomes that agents are provably unable to bring about.

Core claim

Defining the inability operator as the negation of the coalition ability operator yields a conservative extension of Coalition Logic. The extension is sound and complete with respect to the standard semantics, and the new operator obeys anti-monotonicity with respect to coalition inclusion, contravariance with respect to goal strength, asymmetric interaction with conjunction and disjunction, failure of superadditivity, non-equivalence to the ability of opposing coalitions, and the equivalence of grand-coalition inability with systemic impossibility.

What carries the argument

The inability operator, defined as the negation of the standard coalition ability operator and interpreted over the same neighbourhood models.

If this is right

  • Larger coalitions are less prone to inability: if a small group cannot achieve a goal, larger groups containing it may still be unable, but the reverse need not hold.
  • Stronger goals are less prone to inability: inability to achieve a weak goal implies inability to achieve any stronger goal.
  • Inability distributes asymmetrically over conjunction and disjunction, unlike standard ability.
  • Inability lacks superadditivity: the inability of two disjoint coalitions to achieve separate goals does not imply their union cannot achieve both.
  • A coalition's inability to achieve a goal is not equivalent to the opposing coalition's ability to prevent it.
  • If the grand coalition is unable to achieve a goal, the goal is systemically impossible in the model.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Specifications in multi-agent safety can now directly encode negative capabilities without indirect workarounds that only rule out ability.
  • The same definitional move could be applied to other ability logics such as ATL to obtain corresponding inability operators without new model classes.
  • Reasoning about constraints and impossibility in distributed systems becomes first-class rather than derived from absence of ability.
  • Verification tools could check both positive and negative agency statements in one uniform language.

Load-bearing premise

That inability is adequately captured simply by negating ability without any additional semantic primitives or dedicated axioms.

What would settle it

A concrete neighbourhood model in which a coalition cannot force a certain outcome yet the derived theorems about inability produce a contradiction with the original ability facts or violate one of the listed modal properties.

read the original abstract

Coalition Logic is primarily concerned with what coalitions can achieve, whereas what coalitions cannot achieve -- their \emph{inability} -- has received comparatively little explicit attention. This asymmetry matters in artificial intelligence and safety-critical multi-agent systems, where one often needs to specify not merely what agents are instructed or disposed not to do, but what they are \emph{unable} to bring about. We develop a conservative extension of Coalition Logic with an explicit inability operator, interpreted as the negation of coalition ability. This operator is introduced as a conservative and formally tractable starting point for studying inability as a modal concept in its own right. We prove soundness, completeness, and conservativity over standard Coalition Logic, and analyse the resulting modal behaviour: anti-monotonicity with respect to coalition inclusion, contravariance with respect to goal strength, asymmetric interaction with conjunction and disjunction, failure of superadditivity, non-equivalence with opponent ability, and the connection between grand-coalition inability and systemic impossibility. Making this definable operator explicit reveals a systematic modal structure governing the limits of agency, and supports reasoning about constraints, negative capabilities, and impossibility in multi-agent systems.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 3 minor

Summary. The paper develops a conservative extension of Coalition Logic by introducing an explicit inability operator interpreted directly as the negation of the coalition ability operator. It claims to prove soundness, completeness, and conservativity with respect to the standard Coalition Logic semantics, and analyzes the resulting modal properties: anti-monotonicity with respect to coalition inclusion, contravariance with respect to goal strength, asymmetric interaction with conjunction and disjunction, failure of superadditivity, non-equivalence with opponent ability, and the connection between grand-coalition inability and systemic impossibility. The extension is motivated by the need to reason explicitly about constraints and negative capabilities in multi-agent systems and AI safety.

Significance. If the central claims hold, the work provides a simple, formally tractable way to make inability explicit within an established logic without introducing new semantic primitives or axioms. This supports direct reasoning about limitations in multi-agent settings, which is relevant for specification and verification tasks. The modal analysis derives non-trivial properties (such as failure of superadditivity and the distinction from opponent ability) as consequences of the base semantics and negation, offering insight into the structure of negative agency. The conservative nature is a strength, as it ensures compatibility with existing Coalition Logic results and tools.

minor comments (3)
  1. The abstract lists six modal properties; the main text should include explicit cross-references (e.g., to lemmas or propositions) showing where each is derived from the semantics of negation and the Coalition Logic axioms.
  2. A short illustrative example in the introduction or semantics section, showing a concrete multi-agent scenario where the inability operator is used to express a constraint that cannot be captured as concisely without it, would improve readability.
  3. Notation for the inability operator (e.g., whether it is written as a new primitive or explicitly as ¬[C]φ) should be fixed consistently from the first use onward.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for their careful reading of the manuscript and for the positive assessment of the contribution. The recommendation to accept is appreciated, as is the recognition that the explicit inability operator provides a simple, conservative way to reason about negative agency without new semantic primitives. No major comments were raised in the report.

Circularity Check

0 steps flagged

No significant circularity identified

full rationale

The paper explicitly defines the inability operator as the negation of the coalition ability operator and proves that the resulting extension is conservative over standard Coalition Logic. Soundness, completeness, and the listed modal properties (anti-monotonicity, contravariance, failure of superadditivity, etc.) are direct logical consequences of this definition together with the semantics of the base logic; they do not reduce any claimed result to a fitted parameter, self-citation chain, or hidden ansatz. No load-bearing step equates a derived theorem to its own input by construction, and the derivation remains self-contained against the external benchmark of Coalition Logic.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The work rests on the established semantics and axioms of Coalition Logic and introduces the inability operator purely as its negation; no free parameters, new entities, or ad-hoc axioms beyond the standard framework are indicated.

axioms (2)
  • standard math Standard Coalition Logic axioms and semantics
    The extension is defined as conservative over standard Coalition Logic.
  • domain assumption Inability operator defined as negation of ability operator
    Explicitly interpreted as the negation of coalition ability as a conservative starting point.

pith-pipeline@v0.9.0 · 5492 in / 1271 out tokens · 65909 ms · 2026-05-07T05:33:11.147118+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Beyond Ability: The Four-Fold Spectrum of Power and the Logic of Full Inability

    cs.LO 2026-05 unverdicted novelty 7.0

    Coalition Logic is extended by defining Full Inability (FI) as a distinct modality alongside Full Control, Positive Determination, and Adverse Determination, with algebraic structure, Klein four-group symmetry, and a ...

Reference graph

Works this paper leans on

49 extracted references · 2 canonical work pages · cited by 1 Pith paper · 1 internal anchor

  1. [1]

    J. L. Austin. Ifs and cans.Proceedings of the British Academy, 42:109–132, 1956

  2. [2]

    Blackwell, 1975

    Anthony Kenny.Will, Freedom and Power. Blackwell, 1975

  3. [3]

    Abilities

    JohnMaier. Abilities. InEdwardN.Zalta, editor,The Stanford Encyclopedia of Philosophy. Spring 2022 edition, 2022. 18

  4. [4]

    Peter B. M. Vranas. I ought, therefore I can.Philosophical Studies, 136(2):167–216, 2007

  5. [5]

    Oxford University Press, 2014

    Nick Bostrom.Superintelligence: Paths, Dangers, Strategies. Oxford University Press, 2014

  6. [6]

    Concrete Problems in AI Safety

    Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mané. Concrete problems in AI safety.arXiv preprint arXiv:1606.06565, 2016

  7. [7]

    arXiv preprint arXiv:2310.19852 , year=

    Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al. AI alignment: A comprehensive survey.arXiv preprint arXiv:2310.19852, 2023

  8. [8]

    Managing extreme AI risks amid rapid progress.Science, 384(6698):842–845, 2024

    Yoshua Bengio, Geoffrey Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Trevor Darrell, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atılım Güneş Baydin, Sheila McIlraith, Qiqi Gao, Ashwin Acharya, and others. Managing extreme AI risks amid rapid progress.Science, 384(6698):842–845, 2024

  9. [9]

    Manipulationofvotingschemes: Ageneralresult.Econometrica, 41(4):587– 601, 1973

    AllanGibbard. Manipulationofvotingschemes: Ageneralresult.Econometrica, 41(4):587– 601, 1973

  10. [10]

    Mark Allen Satterthwaite. Strategy-proofness and Arrow’s conditions: Existence and cor- respondence theorems for voting procedures and social welfare functions.Journal of Eco- nomic Theory, 10(2):187–217, 1975

  11. [11]

    A modal logic for coalitional power in games.Journal of Logic and Compu- tation, 12(1):149–166, 2002

    Marc Pauly. A modal logic for coalitional power in games.Journal of Logic and Compu- tation, 12(1):149–166, 2002

  12. [12]

    PhD thesis, University of Amsterdam, 2001

    Marc Pauly.Logic for Social Software. PhD thesis, University of Amsterdam, 2001

  13. [13]

    Henzinger, and Orna Kupferman

    Rajeev Alur, Thomas A. Henzinger, and Orna Kupferman. Alternating-time temporal logic.Journal of the ACM, 49(5):672–713, 2002

  14. [14]

    Wiley, 2nd edition, 2009

    Michael Wooldridge.An Introduction to MultiAgent Systems. Wiley, 2nd edition, 2009

  15. [15]

    Logicsforreasoningaboutstrategic abilities in multi-agent systems

    NilsBulling, ValentinGoranko, andWojciechJamroga. Logicsforreasoningaboutstrategic abilities in multi-agent systems. In Hans van Ditmarsch, Joseph Y. Halpern, Wiebe van der Hoek, and Barteld Kooi, editors,Handbook of Epistemic Logic, pages 253–312. College Publications, 2015

  16. [16]

    Cooperation, knowledge, and time: Alternating-time temporal epistemic logic and its applications.Studia Logica, 75(1):125– 157, 2003

    Wiebe van der Hoek and Michael Wooldridge. Cooperation, knowledge, and time: Alternating-time temporal epistemic logic and its applications.Studia Logica, 75(1):125– 157, 2003

  17. [17]

    Coalition logic with individual, distributed and common knowledge.Journal of Logic and Computation, 29(7):1041–1069, 2019

    Thomas Ågotnes and Natasha Alechina. Coalition logic with individual, distributed and common knowledge.Journal of Logic and Computation, 29(7):1041–1069, 2019

  18. [18]

    Group and individual reasoning about knowledge and ability.Artificial Intelligence, 310:103752, 2022

    Thomas Ågotnes and Wojciech Jamroga. Group and individual reasoning about knowledge and ability.Artificial Intelligence, 310:103752, 2022

  19. [19]

    Reasoning about resource-bounded agents.Journal of Logic and Computation, 24(3):661–697, 2014

    Natasha Alechina, Stéphane Demri, and Brian Logan. Reasoning about resource-bounded agents.Journal of Logic and Computation, 24(3):661–697, 2014

  20. [20]

    On the boundary of decidability: Decid- able model-checking for a fragment of resource agent logic

    Natasha Alechina, Nils Bulling, and Brian Logan. On the boundary of decidability: Decid- able model-checking for a fragment of resource agent logic. InProceedings of IJCAI 2017, pages 1494–1500, 2017

  21. [21]

    Coalition logic with con- straints on actions

    Valentin Goranko, Munyque Mittelmann, and Giuseppe Perelli. Coalition logic with con- straints on actions. InProceedings of AAMAS 2024, pages 701–709, 2024. 19

  22. [22]

    A logic of individual and collective agency with contingent action types.Artificial Intelligence, 311:103770, 2022

    Emiliano Lorini and Andreas Herzig. A logic of individual and collective agency with contingent action types.Artificial Intelligence, 311:103770, 2022

  23. [23]

    Fabio Mogavero, Aniello Murano, Giuseppe Perelli, and Moshe Y. Vardi. Reasoning about strategies: On the model-checking problem.ACM Transactions on Computational Logic, 15(4):34:1–34:47, 2014

  24. [24]

    Verification of strategy logic specifications

    Edoardo Caravagna, Alessio Lomuscio, Aniello Murano, and Giuseppe Perelli. Verification of strategy logic specifications. InProceedings of IJCAI 2023, pages 6575–6583, 2023

  25. [25]

    Cornell University Press, 1962

    Jaakko Hintikka.Knowledge and Belief: An Introduction to the Logic of the Two Notions. Cornell University Press, 1962

  26. [26]

    Halpern and Yoram Moses

    Joseph Y. Halpern and Yoram Moses. A guide to the modal logics of knowledge and belief. InProceedings of IJCAI 1985, pages 480–490, 1985

  27. [27]

    Ronald Fagin and Joseph Y. Halpern. Belief, awareness, and limited reasoning.Artificial Intelligence, 34(1):39–76, 1988

  28. [28]

    A logic for ignorance.Electronic Notes in Theoretical Computer Science, 85(2):117–133, 2004

    Wiebe van der Hoek and Alessio Lomuscio. A logic for ignorance.Electronic Notes in Theoretical Computer Science, 85(2):117–133, 2004

  29. [29]

    A logical modeling of severe igno- rance.Journal of Philosophical Logic, 52(4):1053–1080, 2023

    Stefano Bonzio, Vincenzo Fano, and Pierluigi Graziani. A logical modeling of severe igno- rance.Journal of Philosophical Logic, 52(4):1053–1080, 2023

  30. [30]

    The logic of ignorance: A proof-theoretic perspective

    Hana Frluckaj and Eric Pacuit. The logic of ignorance: A proof-theoretic perspective. Studia Logica, 112(2):341–372, 2024

  31. [31]

    Standardstate-spacemodelspreclude unawareness.Econometrica, 66(1):159–173, 1998

    EddieDekel, BartonL.Lipman, andAldoRustichini. Standardstate-spacemodelspreclude unawareness.Econometrica, 66(1):159–173, 1998

  32. [32]

    Schipper

    Burkhard C. Schipper. Awareness. In Hans van Ditmarsch, Joseph Y. Halpern, Wiebe van der Hoek, and Barteld Kooi, editors,Handbook of Epistemic Logic, pages 147–203. College Publications, 2015

  33. [33]

    Awareness logic: A Kripke-based ren- dition.Journal of Philosophical Logic, 53:1–35, 2024

    Franz Dietrich, Christian List, and Marcus Pivato. Awareness logic: A Kripke-based ren- dition.Journal of Philosophical Logic, 53:1–35, 2024

  34. [34]

    Halpern and Leandro C

    Joseph Y. Halpern and Leandro C. Rêgo. Reasoning about knowledge of unawareness. Games and Economic Behavior, 88:100–120, 2014

  35. [35]

    Model checking strate- gic ability under imperfect information is undecidable.Journal of Artificial Intelligence Research, 76:1–35, 2023

    Wojciech Jamroga, Damian Leśkiewicz, and Artur Niewiadomski. Model checking strate- gic ability under imperfect information is undecidable.Journal of Artificial Intelligence Research, 76:1–35, 2023

  36. [36]

    Game-theoretic semantics for ATL+ with applications to model checking

    Valentin Goranko, Antti Kuusisto, and Raine Rönnholm. Game-theoretic semantics for ATL+ with applications to model checking. InProceedings of AAMAS 2022, pages 559– 567, 2022

  37. [37]

    Comparing semantics of logics for multi-agent systems.Synthese, 139(2):241–280, 2004

    Valentin Goranko and Wojciech Jamroga. Comparing semantics of logics for multi-agent systems.Synthese, 139(2):241–280, 2004

  38. [38]

    Chellas.Modal Logic: An Introduction

    Brian F. Chellas.Modal Logic: An Introduction. Cambridge University Press, 1980

  39. [39]

    CambridgeUniversity Press, 2001

    PatrickBlackburn, MaartendeRijke, andYdeVenema.Modal Logic. CambridgeUniversity Press, 2001. 20

  40. [40]

    Enderton.A Mathematical Introduction to Logic

    Herbert B. Enderton.A Mathematical Introduction to Logic. Academic Press, 2nd edition, 2001

  41. [41]

    Osborne and Ariel Rubinstein.A Course in Game Theory

    Martin J. Osborne and Ariel Rubinstein.A Course in Game Theory. MIT Press, 1994

  42. [42]

    Oxford University Press, 2001

    Nuel Belnap, Michael Perloff, and Ming Xu.Facing the Future: Agents and Choices in Our Indeterminist World. Oxford University Press, 2001

  43. [43]

    Horty.Agency and Deontic Logic

    John F. Horty.Agency and Deontic Logic. Oxford University Press, 2001

  44. [44]

    Using STIT theory to talk about strategies

    Jan Broersen and Andreas Herzig. Using STIT theory to talk about strategies. In Johan van Benthem, Sujata Ghosh, and Rineke Verbrugge, editors,Models of Strategic Reasoning, pages 137–173. Springer, 2015

  45. [45]

    Halpern, Yoram Moses, and Moshe Y

    Ronald Fagin, Joseph Y. Halpern, Yoram Moses, and Moshe Y. Vardi.Reasoning About Knowledge. MIT Press, 1995

  46. [46]

    Arrow.Social Choice and Individual Values

    Kenneth J. Arrow.Social Choice and Individual Values. Wiley, 1951

  47. [47]

    Holden-Day, 1970

    Amartya Sen.Collective Choice and Social Welfare. Holden-Day, 1970

  48. [48]

    Procaccia, editors

    Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang, and Ariel D. Procaccia, editors. Handbook of Computational Social Choice. Cambridge University Press, 2016

  49. [49]

    Cambridge University Press, 2007

    Hans van Ditmarsch, Wiebe van der Hoek, and Barteld Kooi.Dynamic Epistemic Logic. Cambridge University Press, 2007. 21