Rational Constraints Research Articles

From group to institutional agency

ABSTRACT We live in an institutional world, where our identity is significantly shaped by our membership in institutional groups (from sports clubs and condo boards to state and international organisations). As such, then, understanding what those groups are and how they affect our reality through their actions is imperative. To that end, some philosophers have taken on the task of elucidating ‘institutional agency' (the capacity of institutional groups to act). Most recently, for example, Michael Bratman has introduced a theory of institutional agency, according to which an institutional group can act if the relevant participants act on an institutional intention (viz., a decision output that satisfies certain rationality constraints). Crucially, he develops this approach on the assumption that ‘planning agency' is the core capacity involved across various forms of human practical organization: individual, social, and institutional. However, this paper shows that while true that planning agency may be a basic element of individual and shared intentionality, it is not so relevant for institutional intentionality. In fact, contra Bratman’s intuitions, it argues that institutional agency is constructed out-of-group attitudes and actions, for which group agency, but not planning agency, is the core capacity.

Preferences: What We Can and Can’t Do with Them

In her Choosing Well, Chrisoula Andreou puts forth an account of instrumental rationality that is revisionary in two respects. First, it changes the goalpost or standard of instrumental rationality to include “categorial” appraisal responses, alongside preferences, which are relational. Second, her account is explicitly diachronic, applying to series of choices as well as isolated ones. Andreou takes both revisions to be necessary for dealing with problematic choice scenarios agents with disorderly preferences might find themselves in. Focusing on problem cases involving cyclical preferences, I will first argue that her first revision is undermotivated once we accept the second. If we are willing to grant that there are diachronic rationality constraints, the preference-based picture can get us further than Andreou acknowledges. I will then turn to present additional grounds for rejecting the preference-based picture. However, these grounds also seem to undermine Andreou’s own appeal to categorial appraisal responses.

Intentions and Inquiry

Abstract This paper defends the Intention Account of Individual Inquiry. On this account, inquiry is best understood by appeal to a ‘question-directed intention’ (QDI), an intention to answer a question broadly construed. This account’s core commitments help meet recent challenges plaguing extant approaches to characterizing inquiry. First, QDIs are the type of mental state central to inquiry, not attitudes like curiosity or wonder. Second, holding a QDI towards a question and acting in service of it constitutes the start of inquiry. Third, controversial norms which mandate a rational inquirer’s ignorance towards the answer to her question can be reformulated and defended by appeal to rational constraints on intention. Fourth, instrumental pressures inquirers face are the standard pressures of plan-rationality. In defending these theses, I show that the Intention Account provides compelling explanations to standing challenges, in ways competitors cannot. It does so by advancing understanding of how our epistemic and practical agency are intertwined.

Two-echelon collaborative many-to-many pickup and delivery problem for agricultural wholesale markets with workload balance

In the context of cooperation distribution among multiple wholesale markets, each customer can place orders with multiple agricultural wholesale markets, and each agricultural wholesale market can supply different products. To improve their distribution efficiency and avoid traffic congestion, cargoes need to be transshipped among collaborative distribution of different agricultural wholesale markets owing to their product heterogeneity. Each agricultural wholesale market undertakes the cost of completing the task for the reassigned customers of finding a balance among them, respectively. Fairness of allocation is achieved through workload balance and individual rationality constraints instead of monetary transfer payments. Aimed at the collaboration problem, a two-echelon collaborative many-to-many pickup and delivery problem with workload balance (2E-MPDP-WB) is presented in this study. A mixed-integer programming model for 2E-MPDP-WB is established, and a two-stage iterative algorithm combining branch-and-bound algorithm and adaptive large neighborhood search algorithm is proposed according to the problem structure. Some valid inequalities are also proposed. Finally, computational experiments show the correctness of the model and effectiveness of the algorithm, and sensitivity analysis is performed from four aspects, namely, costs before and after collaboration, workload balance, market geographical distribution, and demand mixing degree. The findings provide management insights for the collaborative distribution of multiple wholesale markets.

What’s so Hard about Hard Choices?

What, exactly, is so hard about hard choices? I suggest that what is distinctively hard about hard choices is that they present us with the volitional difficulty of putting ourselves behind an alternative and thereby making it true of ourselves that we have most reason to do one thing rather than another. Making it true through your commitments that, for instance, you have most reason to be a philosopher rather than a lawyer makes the choice between the careers hard. This answer is in contrast to that of Sergio Tenenbaum, who understands the hardness of a hard choice as a deliberative difficulty in specifying our alternatives and ends in ways that conform with certain proposed constraints of rationality. For Tenenbaum, the hardness of hard choices is not distinctive to such choices but is a general difficulty rational agents face when they need to further specify their alternatives and ends, even if the choice is easy.

Ultra-wide temperature range aqueous electrolyte through local aggregation anchoring active water towards practical aqueous zinc metal battery

The key to realizing the application of aqueous electrolytes to extreme environments lies in rational constraints on active water. Herein, a strategy for local aggregation electrolyte (LA-Zn(OTf)2) with dynamic anchoring of active H2O is proposed and achieved by precisely regulating the molecular weight and addition amount of organic long chains enriched with hydrogen-bond acceptors. The results show that the saturated vapor pressure of LA-Zn(OTf)2 is reduced by 16 % at 90 °C and it does not freeze at -30 °C, achieving a wide operating temperature range of 120 °C. In LA-Zn(OTf)2, the local aggregation of Zn2+, solvent water, and ether bonding groups form a contact ion pair (CIP) structure, which enables rapid and stable deposition of Zn metal. Moreover, a stable organic-inorganic solid electrolyte interface (SEI) is formed to suppress corrosion and hydrogen evolution. At room temperature, the Zn|LA-Zn(OTf)2|Zn symmetric cell is stably cycled for over 4000 h at 1 mA cm-2. At the extreme temperatures of 90 and -30 °C, the Zn|LA-Zn(OTf)2|NVO full cells achieve stable cycling more than 1400 and 2000 cycles at 0.5 A g-1, respectively, and the capacity retention rates are 70.1 % and 80.5 %, respectively.

Federated learning in smart home: A dynamic contract-based incentive approach with task preferences

Federated Learning (FL) is a new type of distributed machine learning paradigm aimed at addressing data privacy and security issues in the Internet of Things (IoT) context. In the training process of federated learning model of smart home, data owners need to constantly update cached data, which lead to resources consumption and service latency. Meanwhile, the update cost of the data owners will change with the passage of time when the model owner requests data update. Therefore, this paper first puts forward an incentive scheme based on two-period dynamic contract theory under the information asymmetry. The scheme can balance the weighted preference of the model owner for age of information (AoI) and service latency, as well as encourage more data owners to participate in model training to increase the utility of model owner. Then we formally prove the feasibility of the proposed dynamic contract, which satisfies the constraints of individual rationality and intertemporal incentive compatibility. The experimental results on MNIST dataset show that the accuracy of the proposed dynamic contract is improved by at least 4% compared with the existing contracts. Additionally, compared with traditional contract and consistent pricing strategy, the model owner obtains more profit from the proposed contract.

Old-age support policy and fertility with strategic bequest motives

This paper presents an analysis of the effects of public old-age support on individuals’ fertility decisions and on the long-term equilibrium in an overlapping generation economy with strategic bequest motives. Parents must pay their adult children at least the reservation wage to receive informal old-age support from them (individual rationality constraint). Formal old-age support is financed through wage taxes on children. The increased present value of formal old-age support tends to increase old-age utility, thereby decreasing the family support demand and decreasing savings for the old age. The increased wage tax reduces the opportunity cost of child-rearing time, thereby increasing the fertility rate. The effects of increased formal old-age support on per-worker capital and labor are indeterminate, as is the effect on the long-term lifetime utility of individuals. A strategic bequest motive might engender a higher fertility rate than that of the social optimum.

Enhancing Data Freshness in Air-Ground Collaborative Heterogeneous Networks through Contract Theory and Generative Diffusion-Based Mobile Edge Computing.

Mobile edge computing is critical for improving the user experience of latency-sensitive and freshness-based applications. This paper provides insights into the potential of non-orthogonal multiple access (NOMA) convergence with heterogeneous air-ground collaborative networks to improve system throughput and spectral efficiency. Coordinated resource allocation between UAVs and MEC servers, especially in the NOMA framework, is addressed as a key challenge. Under the unrealistic assumption that edge nodes contribute resources indiscriminately, we introduce a two-stage incentive mechanism. The model is based on contract theory and aims at optimizing the utility of the service provider (SP) under the constraints of individual rationality (IR) and incentive compatibility (IC) of the mobile user. The block coordinate descent method is used to refine the contract design and complemented by a generative diffusion model to improve the efficiency of searching for contracts. During the deployment process, the study emphasizes the positioning of UAVs to maximize SP effectiveness. An improved differential evolutionary algorithm is introduced to optimize the positioning of UAVs. Extensive evaluation shows our approach has excellent effectiveness and robustness in deterministic and unpredictable scenarios.

Probabilistic coherence, logical consistency, and Bayesian learning: Neural language models as epistemic agents.

It is argued that suitably trained neural language models exhibit key properties of epistemic agency: they hold probabilistically coherent and logically consistent degrees of belief, which they can rationally revise in the face of novel evidence. To this purpose, we conduct computational experiments with rankers: T5 models [Raffel et al. 2020] that are pretrained on carefully designed synthetic corpora. Moreover, we introduce a procedure for eliciting a model's degrees of belief, and define numerical metrics that measure the extent to which given degrees of belief violate (probabilistic, logical, and Bayesian) rationality constraints. While pretrained rankers are found to suffer from global inconsistency (in agreement with, e.g., [Jang et al. 2021]), we observe that subsequent self-training on auto-generated texts allows rankers to gradually obtain a probabilistically coherent belief system that is aligned with logical constraints. In addition, such self-training is found to have a pivotal role in rational evidential learning, too, for it seems to enable rankers to propagate a novel evidence item through their belief systems, successively re-adjusting individual degrees of belief. All this, we conclude, confirms the Rationality Hypothesis, i.e., the claim that suitable trained NLMs may exhibit advanced rational skills. We suggest that this hypothesis has empirical, yet also normative and conceptual ramifications far beyond the practical linguistic problems NLMs have originally been designed to solve.

Collective argumentation with topological restrictions: the case of aggregating abstract argumentation frameworks

AbstractCollective argumentation is the process of reaching a collective decision that is acceptable to the group in a debate. We introduce the notion of topological restriction to enrich the study of collective argumentation. Topological restrictions are rational constraints assumed to be satisfied by individual agents. We assume that in a debate, for every pair of arguments under consideration, every agent indicates whether the first argument attacks the second, i.e. an agent’s argumentative stance is characterized as an argumentation framework, and only argumentation frameworks that satisfy topological restrictions are allowed. The topological restrictions we consider in this paper include various topological properties in the literature, such as acyclicity, symmetry, coherence and determinedness, as well as three topological restrictions that generalize classic social-choice-theoretic domain conditions. We show that when the profile of the argumentation frameworks provided by the agents satisfies topological restrictions, impossibility results during aggregation can be avoided. Furthermore, if a profile is topologically restricted with respect to restrictions that generalize domain conditions, then the majority rule preserves several desirable properties during aggregation.

Bounded Rationality and Control

The rationality constraint condition is formulated, which states that when solving control, computing and communication problems ($C^3$) together, real-time requirements may not make it possible to find the optimal solution (control action), forcing the use of almost optimal solutions (the best found with the existing restrictions on the search procedure). This condition connects and demonstrates the unity and deep interconnection of such concepts common in management and optimization as: necessary diversity, limited rationality, analytical complexity, heuristics, records in real-time optimization. In relation to the problem of institutional management of organizational and technical systems, a number of examples of solving problems of minimizing error or complexity, as well as searching for: critical bandwidth of the communication channel, critical computing rate and the maximum number of controlled subsystems are given.

Negation, Truth and Falsity

The present article includes thematically connected questions on negation in the areas of the philosophy of logic, philosophical logic and metaphysics. It highlights a central problem negation poses to a certain area of philosophy. The purpose of the article is also to analyze negation in the areas of the philosophy of logic, philosophical logic and metaphysics. It highlights a central problem negation poses to a certain area of philosophy. It includes historical references, puts the problems discussed into context, and ties together a number of the main themes and problems. The investigation discusses the problem of logical revisionism and whether there is any room for genuine disagreement, and hence shared meaning, between the classicist and deviant’s respective uses of ‘not’. If there is not, revision is impossible. We argue that revision is indeed possible and provide an account of negation as contradictoriness according to which a number of alleged negations are declared genuine. Among them are the negations of FDE (First-Degree Entailment) and a wide family of other relevant logics, LP (Priest’s dialetheic “Logic of Paradox”), Kleene weak and strong 3-valued logics with either “exclusion” or “choice” negation, and intuitionistic logic. We also discuss the problem of furnishing intuitionistic logic with an empirical negation for adequately expressing claims of the form ‘A is undecided at present’ or ‘A may never be decided’ the latter of which has been argued to be intuitionistically inconsistent. We reveal the importance of various notions of consequence-as-s-preservation where s may be falsity (versus untruth), indeterminacy or some other semantic (or “algebraic”) value, in formulating rationality constraints on speech acts and propositional attitudes such as rejection, denial and dubitability. The article provides an account of the nature of truth values regarded as objects. It is argued that only truth exists as the maximal truthmaker. The consequences this has for semantics representationally construed are considered and it is argued that every logic, from classical to non-classical, is gappy. Moreover, a truthmaker theory is developed whereby only positive truths, an account of which is also developed therein, have truthmakers. We investigate the definability of negation as “absolute” impossibility, i.e. where the notion of necessity or possibility in question corresponds to the global modality.

EDT0L solutions to equations in group extensions

We show that the class of groups where EDT0L languages can be used to describe solution sets to systems of equations is closed under direct products, wreath products with finite groups, and passing to finite index subgroups. We also add the class of groups that contain a direct product of hyperbolic groups as a finite index subgroup to the list of groups where solutions to systems of equations can be expressed as an EDT0L language. This includes dihedral Artin groups. We also show that the systems of equations with rational constraints in virtually abelian groups have EDT0L solutions, and the addition of recognisable contraints to any system preserves the property of having EDT0L solutions. These EDT0L solutions are expressed with respect to quasigeodesic normal forms. We discuss the space complexity in which EDT0L systems for these languages can be constructed.

The impact of board of directors’ characteristics on the internationalization of family SMEs

Family small and medium-sized enterprises (SMEs) face both general bounded rationality challenges and a unique expression of bounded rationality in their internationalization process: the bifurcation bias, a concept aligned with modern transaction cost theory (TCT). We argue that efficient governance in family SMEs, and especially features of the Board of Directors’ composition, can help alleviate bounded rationality. Complementing TCT with upper echelons theory (UET), we investigate which Board characteristics in family SMEs contribute to efficient governance and the ensuing strategy decisions. We focus specifically on strategy decisions in the internationalization sphere. Our empirical analysis of survey data from 328 Belgian family SMEs, operating out of a small open economy, reveals that family SMEs internationalize more if their Boards are ‘open’, ‘inclusive’, ‘experienced’ and ‘active’. These Board characteristics, all reflective of efficient governance, i.e., providing the Board with the capacity to alleviate bounded rationality constraints, positively contribute to internationalization, especially (and perhaps paradoxically) when the family SME is managed by a CEO who is also a family member.

Outside options in neutral allocation of discrete resources

Serial dictatorships have emerged as the canonical simple mechanisms in the literature on the allocation of indivisible goods without transfers. They are the only neutral and group-strategy-proof mechanisms in environments in which agents have no outside options and hence no individual rationality constraints (Svensson in Soc Choice Welfare 16:557–567, 1999). Accounting for outside options and individual rationality constraints, our main result constructs the class of group-strategy-proof, neutral, and non-wasteful mechanisms. These mechanisms are also Pareto efficient and we call them binary serial dictatorships. The abundance of the outside option—anybody who wants can opt out to get it—is crucial for our result.

Cognitive phenomenology: in defense of recombination

ABSTRACT The cognitive experience view of thought holds that the content of thought is determined by its cognitive-phenomenal character. Adam Pautz argues that the cognitive experience view is extensionally inadequate: it entails the possibility of mix-and-match cases, where the cognitive-phenomenal properties that determine thought content are combined with different sensory-phenomenal and functional properties. Because mix-and-match cases are metaphysically impossible, Pautz argues, the cognitive experience view should be rejected. This paper defends the cognitive experience view from Pautz’s argument. I build on resources in the philosophy of mind literature to show that cognitive-phenomenal properties are modally independent from sensory-phenomenal and functional properties. The result is that mix-and-match cases, though modally remote, are metaphysically possible. The possibility of mix-and-match cases allows us to move from defensive posture to a critical one: it poses problems for any theory of content that imposes rationality constraints, including Pautz’s positive view, phenomenal functionalism.

Audit report information improvement and earnings management

AbstractIncreasing the disclosure of key audit matters (KAMs) has been an important change in audit reports in recent years. After the implementation of this policy, what changes have taken place in the behaviour of auditors after the implementation of this policy? What impact has it had on the audit report? A series of problems deserve systematic analysis and empirical testing. This paper examines the relationship between the communication of KAMs and earnings management. We examined quasi‐natural experimental data shaped by new auditing standards issued by the Ministry of Finance of China on 23 December 2016. The new auditing standards have been implemented in phases for the listed companies. We find that (1) communicating KAMs in audit reports restrains the auditor's motivational reasoning behaviour by triggering rationality constraints and improves the auditor's professional scepticism, thus improving audit quality and significantly reducing the company's accrued earnings management level. (2) The influence of communicating KAMs on earnings management is more significant for sampled firms with high external financing dependence and low marketization, revealing its supplementary role in the existing corporate governance mechanism. The findings of this paper enrich existing research on KAMs and supplement important empirical evidence from the Chinese market for assessing the effects of audit reporting reforms worldwide.

Are we justified attributing a mistake in diagnosis to an AI diagnostic system?

Responsible professional use of AI implies the readiness to respond to and address—in ethically appropriate manner—harm that may be associated with such use. This presupposes the ownership of mistakes. In this paper, I ask if a mistake in AI-enhanced decision making—such as AI-aided medical diagnosis—can be attributed to the AI system itself, and answer this question negatively. I will explore two options. If AI systems are merely tools, then we are never justified to attribute mistakes to them, because their failing does not meet rational constraints on being mistaken. If, for the sake of the argument, we assume that AI systems are not (mere) tools, then we are faced with certain challenges. The first is the burden to explain what this more-than-a-tool role of an AI system is, and to establish justificatory reasons for the AI system to be considered as such. The second is to prove that medical diagnosis can be reduced to the calculations by AI system without any significant loss to the purpose and quality of the diagnosis as a procedure. I will conclude that the problem of the ownership of mistakes in hybrid decision making necessitates new forms of epistemic responsibilities.

Learning to branch in the generation maintenance scheduling problem

To maximize the reliability index of a power system, this study modeled a generation maintenance scheduling problem that considers the network security constraints and rationality constraints of the generation maintenance practice in a power system. In view of the computational complexity of the generation maintenance scheduling model, a variable selection method based on a support vector machine (SVM) is proposed to solve the 0–1 mixed integer programming problem (MIP). The algorithm observes and collects data from the decisions made by strong branching (SB) and then learns a surrogate function that mimics the SB strategy using a support vector machine. The learned ranking function is then used for variable branching during the solution process of the model. The test case showed that the proposed variable selection algorithm — based on the features of the proposed generation maintenance scheduling problem during branch-and-bound — can increase the solution efficiency of the generation-scheduling model on the premise of guaranteed accuracy.