In multi-armed bandit problems, information acquired from experimentation is valuable because it tells the agent whether to select a particular option again in the future. This article tests whether people undervalue this information because they are ambiguity averse, or have a distaste for uncertainty about the average quality of each alternative. It is shown that ambiguity averse agents have lower than optimal Gittins indexes, appearing to undervalue information from experimentation, but are willing to pay more than (...) ambiguity neutral agents to learn the true mean of the payoff distribution, appearing to overvalue objectively given information. This prediction is tested with a laboratory experiment that elicits a Gittins index and a willingness to pay on six two-armed bandits. Consistent with the predictions of ambiguity aversion, the Gittins indexes are significantly lower than optimal and willingnesses to pay are significantly higher than optimal. (shrink)

In February 2020, as covid-19 infections spread to more than fifty countries, public health officials needed to recommend how the public could protect themselves, balancing safety and urgency. But there was very little data since this novel virus had only been identified three months prior. How could public health officials decide with insufficient data? The multi-armed bandit problem of computer science offers adaptive decision-making procedures that can achieve both safety and urgency. These adaptive methods balance learning information (...) (exploring) with using information (exploiting), adjusting the balance toward learning when uncertainty is high (March 1991; Kaelbling et al. 1996). Related methods are already used in adaptive clinical trials for pharmaceuticals (Pallmann et al. 2018). But we still need to develop these methods for non-pharmaceutical interventions, as I will illustrate with a case study of public mask-wearing to reduce the spread of covid-19. Public health pronouncements impact future learning. (shrink)

Decision making in noisy and changing environments requires a fine balance between exploiting knowledge about good courses of action and exploring the environment in order to improve upon this knowledge. We present an experiment on a restless bandit task in which participants made repeated choices between options for which the average rewards changed over time. Comparing a number of computational models of participants’ behavior in this task, we find evidence that a substantial number of them balanced exploration and exploitation (...) by considering the probability that an option offers the maximum reward out of all the available options. (shrink)

The aim of this paper is to study the monotonicity properties with respect to the probability distribution of the state processes, of optimal decisions in bandit decision problems. Orderings of dynamic discrete projects are provided by extending the notion of stochastic dominance to stochastic processes.

We evaluate the asymptotic performance of boundedly-rational strategies in multi-armed bandit problems, where performance is measured in terms of the tendency (in the limit) to play optimal actions in either (i) isolation or (ii) networks of other learners. We show that, for many strategies commonly employed in economics, psychology, and machine learning, performance in isolation and performance in networks are essentially unrelated. Our results suggest that the appropriateness of various, common boundedly-rational strategies depends crucially upon the (...) social context (if any) in which such strategies are to be employed. (shrink)

We consider a situation where an individual is facing an uncertain situation, but may costly alter his knowledge of the uncertainties. We study in this context how risk aversion may modify the individual search behavior. We consider a one-armed bandit problem (where one arm is safe and the other is risky) and study how the agent risk aversion can change the sequence of arms selected. The main result is that when the utility function is more concave, the agent (...) has more chances to select the safe arm. We also discuss how search is affected by risk aversion. (shrink)

We consider a situation where an individual is facing an uncertain situation, but may costly alter his knowledge of the uncertainties. We study in this context how risk aversion may modify the individual search behavior. We consider a one-armed bandit problem (where one arm is safe and the other is risky) and study how the agent risk aversion can change the sequence of arms selected. The main result is that when the utility function is more concave, the agent (...) has more chances to select the safe arm. We also discuss how search is affected by risk aversion. (shrink)

The literature on the wrong kind of reason problem largely assumes that such reasons pose only a theoretical problem for certain theories of value rather than a practical problem. Since the normative force of the canonical examples is obvious, the only difficulty is to identify what reasons of the right and wrong kind have in common without circularity. This chapter argues that in addition to the obvious WKRs on which the literature focuses, there are also more interesting WKRs that do (...) not overtly refer to the advantages of having some evaluative attitude. Instead they refer to features of the object that bear on the propriety of having certain attitudes toward it. What is interesting about these cases is that their normative force is opaque. It can be clear that some consideration bears on whether or not to feel shame, pity, or amusement, for example, but unclear just how it does so—specifically, whether the consideration helps make the object of the attitude shameful, pitiable, or funny. The problems caused by WKRs are ubiquitous, and they outstrip the wrong kind of reason problem as it has ordinarily been conceived, since extant solutions to the technical problem offer no help resolving the opacity of normative force. (shrink)

This discussion explores the moral psychology and metaethics of Michael Slote's Moral Sentimentalism. I argue that his account of empathy has an important lacuna, because the sense in which an empathizer feels the same feeling that his target feels requires explanation, and the most promising candidates are unavailable to Slote. I then argue that the (highly original) theory of moral approval and disapproval that Slote develops in his book is implausible, both phenomenologically and for the role it accords to empathy. (...) Finally, I suggest that these problems in moral psychology undermine Slote's metaethical argument for identifying rightness and wrongness with agential warmth and coldness in action. (shrink)

Evolutionary attempts to explain morality tend to say very little about what morality is. If evolutionary game theory aspires not merely to solve the ‘problem of altruism', but to explain human morality or justice in particular, it requires an appropriate conception of that subject matter. This paper argues that one plausible conception of morality (a sanction-based conception) creates some important constraints on the kinds of evolutionary explanations that can shed light on morality. Game theoretic approaches must either meet these constraints, (...) or defend an alternative conception of morality. Skyrms’ model of the evolution of justice is found to violate the constraints imposed by the sanction-based conception. (shrink)

Background: There is a growing interest in using cognitive behavioural therapy with people who have Asperger Syndrome and comorbid mental health problems. Aims: To examine whether modified group CBT for clinically significant anxiety in an AS population is feasible and likely to be efficacious. Method: Using a randomised assessor-blind trial, 52 individuals with AS were randomised into a treatment arm or a waiting-list control arm. After 24 weeks, those in the waiting-list control arm received treatment, while those initially randomised (...) to treatment were followed-up for 24 weeks. Results: The conversion rate for this trial was high, while attrition was 13%. After 24 weeks, there was no significant difference between those randomised to the treatment arm compared to those randomised to the waiting-list control arm on the primary outcome measure, the Hamilton Rating Scale for Anxiety. Conclusions: Trials of psychological therapies with this population are feasible. Larger definitive trials are now needed. Declaration of Interest: None Trial Registration: ISRCTN 30265294, UKCRN 8370. (shrink)

How do people pursue rewards in risky environments, where some outcomes should be avoided at all costs? We investigate how participant search for spatially correlated rewards in scenarios where one must avoid sampling rewards below a given threshold. This requires not only the balancing of exploration and exploitation, but also reasoning about how to avoid potentially risky areas of the search space. Within risky versions of the spatially correlated multi‐armed bandit task, we show that participants’ behavior is (...) aligned well with a Gaussian process function learning algorithm, which chooses points based on a safe optimization routine. Moreover, using leave‐one‐block‐out cross‐validation, we find that participants adapt their sampling behavior to the riskiness of the task, although the underlying function learning mechanism remains relatively unchanged. These results show that participants can adapt their search behavior to the adversity of the environment and enrich our understanding of adaptive behavior in the face of risk and uncertainty. (shrink)

Multiarm bandit problems have been used to model the selection of competing scientific theories by boundedly rational agents. In this paper, I define a variable-arm bandit problem, which allows the set of scientific theories to vary over time. I show that Roth-Erev reinforcement learning, which solves multiarm bandit problems in the limit, cannot solve this problem in a reasonable time. However, social learning via preferential attachment combined with individual reinforcement learning which discounts the past, does.

Applying causal methods to fields such as healthcare, marketing, and economics receives increasing interest. In particular, optimising the individual-treatment-effect – often referred to as uplift modelling – has peaked in areas such as precision medicine and targeted advertising. While existing techniques have proven useful in many settings, they suffer vividly in a dynamic environment. To address this issue, we propose a novel optimisation target that is easily incorporated in bandit algorithms. Incorporating this target creates a causal model which we (...) name an uplifted contextual multi-armed bandit. Experiments on real and simulated data show the proposed method to effectively improve upon the state-of-the-art. All our code is made available online at https://github.com/vub-dl/u-cmab. (shrink)

Probability updating via Bayes' rule often entails extensive informational and computational requirements. In consequence, relatively few practical applications of Bayesian adaptive control techniques have been attempted. This paper discusses an alternative approach to adaptive control, Bayesian in spirit, which shifts attention from the updating of probability distributions via transitional probability assessments to the direct updating of the criterion function, itself, via transitional utility assessments. Results are illustrated in terms of an adaptive reinvestment two-armed bandit problem.

Through numbers of studies on the formation of equivalence relations and causal induction, it is known that human beings tend to consider conditional statements ``if p then q " as biconditional statements ``if and only if p then q ": we call the tendency to perceive ``if p then q " as ``if q then p " the ``symmetry bias". On the other hand, many studies on children's word learning have pointed out that children tend to expect each object has (...) only one label. This is so-called the ``mutual exclusivity bias". This bias implies. (shrink)

This article defends the view that markets in education need to be restricted, in light of the problem posed by what I call the ‘educational arms race’. Markets in education have a tendency to distort an important balance between education’s role as a gatekeeper – its ‘screening’ function – and its role in helping children develop as part of a preparation for adult life. This tendency is not merely a contingent fact about markets: It can be traced to ways in (...) which education is a partly positional good and how markets respond to demand for positional goods over non-positional goods. The problem with arms races is that they allow markets to facilitate wider use of defection in a collective action problem. Using these claims, I argue that markets in education have a distinctive tendency to become objectionably exploitative. I conclude by applying some of my conclusions to illuminate various egalitarian claims about justice in education. (shrink)

In this paper, a complex non- linear programming problem with the two parts (real and imaginary) is considered. The efficient and proper efficient solutions in terms of optimal solutions of related appropriate scalar optimization problems are characterized. Also, the Kuhn-Tuckers' conditions for efficiency and proper efficiency are derived. This paper is divided into two independently parts: The first provides the relationships between the optimal solutions of a complex single-objective optimization problem and solutions of two related real programming problems. (...) The second part is concerned with the theory of a multi-objective optimization in complex space. (shrink)

Making adaptive choices between solution strategies is a central element of contemporary mathematics education. However, previous studies signal that students make suboptimal choices between mental and written strategies to solve division problems. In particular, some students of a lower math ability level appear inclined to use mental strategies that lead to lower performance. The current study uses a pretest-training-posttest design to investigate the extent to which these students’ choices for written strategies and performance may be increased. Sixth graders of (...) below-average mathematics level (N = 147) participated in one of two training conditions: an explicit-scaffolding training designed to promote writing down calculations or a practice-only training where strategy use was not explicitly targeted. Written strategy choices and performance increased considerably from pretest to posttest for students in both training conditions, but not in different amounts. Exploratory results suggest that students’ strategy choices may also be affected by their attitudes and beliefs and the sociocultural context regarding strategy use. (shrink)

The pigeon-inspired optimization algorithm is a category of a newly proposed swarm intelligence-based algorithm that belongs to the population-based solution technique. The MKP is a class of complex optimization problems that have many practical applications in the fields of engineering and sciences. Due to the practical applications of MKP, numerous algorithmic-based methods like local search and population-based search algorithms have been proposed to solve the MKP in the past few decades. This paper proposes a modified binary pigeon-inspired optimization algorithm (...) named (Modified-BPIO) for the 0 - 1 multidimensional knapsack problem (MKP). The utilization of the binary pigeon-inspired optimization (BPIO) for solving the multidimensional knapsack problem came with huge success. However, it can be observed that the BPIO converges prematurely due to lost diversity during the search activities. Given the above, the crossover operator is integrated with the landmark component of the BPIO to improve the diversity of the solution space. The MKP benchmarks from the Operations Research (OR) library are utilized to test the performance of the proposed binary method. Experimentally, it is concluded that the proposed Modified-BPIO has a better performance when compared with the BPIO and existing state-of-the-arts that worked on the same MKP benchmarks. (shrink)

Embodied cognition postulates a bi-directional link between the human body and its cognitive functions. Whether this holds for higher cognitive functions such as problem solving is unknown. We predicted that arm movement manipulations performed by the participants could affect the problem-solving solutions. We tested this prediction in quantitative reasoning tasks that allowed two solutions to each problem. In two studies with healthy adults, we found an effect of problem-congruent movements on problem solutions. Consistent with embodied cognition, sensorimotor information gained via (...) right or left arm movements affects the solution in different types of problem-solving tasks. (shrink)

The organism is one of the fundamental concepts of biology and has been at the center of many discussions about biological individuality, yet what exactly it is can be confusing. The definition that we find generally useful is that an organism is a unit in which all the subunits have evolved to be highly cooperative, with very little conflict. We focus on how often organisms evolve from two or more formerly independent organisms. Two canonical transitions of this type—replicators clustered in (...) cells and endosymbiotic organelles within host cells—demonstrate the reality of this kind of evolutionary transition and suggest conditions that can favor it. These conditions include co-transmission of the partners across generations and rules that strongly regulate and limit conflict, such as a fair meiosis. Recently, much attention has been given to associations of animals with microbes involved in their nutrition. These range from tight endosymbiotic associations like those between aphids and Buchnera bacteria, to the complex communities in animal intestines. Here, starting with a reflection about identity through time, we consider the distinctions between these kinds of animal–bacteria interactions and describe the criteria by which a few can be considered jointly organismal but most cannot. (shrink)

Joe Horton’s all-or-nothing problem concerns a situation in which it is morally permissible to do nothing and to save two people but not to save only one. This description seems to entail that we should do nothing rather than save only one. I object to Horton’s solution and challenge a principle he draws attention to, which is required to generate the problem but which Horton regards as beyond dispute.

The aim of this paper is to study the monotonicity properties with respect to the probability distribution of the state processes, of optimal decisions in bandit decision problems. Orderings of dynamic discrete projects are provided by extending the notion of stochastic dominance to stochastic processes.

Cocreating meaning in collaboration is challenging. Success is often determined by people's abilities to coordinate their language to converge upon shared mental representations. Here we explore one set of low‐level linguistic behaviors, linguistic alignment, that both emerges from, and facilitates, outcomes of high‐level convergence. Linguistic alignment captures the ways people reuse, that is, “align to,” the lexical, syntactic, and semantic forms of others' utterances. Our focus is on the temporal change of multi‐level linguistic alignment, as well as how alignment (...) is related to communicative outcomes within a unique collaborative problem‐solving paradigm. The primary task, situated within a virtual educational video game, requires creative thinking between three people where the paths for possible solutions are highly variable. We find that over time interactions are marked by decreasing lexical and syntactic alignment, with a trade‐off of increasing semantic alignment. However, greater semantic alignment does not translate into better team performance. Overall, these findings provide greater clarity on the role of linguistic coordination within complex and dynamic collaborative problem‐solving tasks. (shrink)

Despite the burgeoning literature on the governance and impact of cross-sector partnerships in the past two decades, the debate on how and when these collaborative arrangements address globally relevant problems and contribute to systemic change remains open. Building upon the notion of wicked problems and the literature on governing such wicked problems, this paper defines harnessing problems in multi-stakeholder partnerships as the approach of taking into account the nature of the problem and of organizing governance (...) processes accordingly. The paper develops an innovative analytical framework that conceptualizes MSPs in terms of three governance processes harnessing three key dimensions of wicked problems. The Roundtable on Sustainable Palm Oil provides an illustrative case study on how this analytical framework describes and explains organizational change in partnerships from a problem-based perspective. The framework can be used to better understand and predict the complex relationships between MSP governance processes, systemic change and societal problems, but also as a guiding tool in organizing governance processes to continuously re-assess the problems over time and address them accordingly. (shrink)

This article develops an unconventional perspective on the utilitarianism of Bentham and Mill in at least four areas. First, it is shown that both authors conceived of utility as irreducibly multi-dimensional, and that Bentham in particular was very much aware of the ambiguity that multi-dimensionality imposes upon optimal choice under the greatest happiness principle. Secondly, I argue that any attribution of intrinsic worth to any form of human behaviour violates the first principles of Bentham's and Mill's utilitarianism, and (...) that this renders both authors immune to the claim by G. E. Moore that they committed a ‘naturalistic fallacy’. Thirdly, in light of these contentions, I find no flaw in Mill's ‘proof of utility’. Fourthly, I use the notion of intrapersonal utility weights to provide an interpretation of Mill's qualitative hedonism that is entirely consistent with his value monism. (shrink)

The main idea of this thesis is multi-descriptional physicalism. According to it, only physical entities are elements of our ontology, and there are different ways to describe them. Higher-level vocabularies (e.g., mental, neurological, biological) truly describe reality. Sentences about higher-level entities are made true by physical entities. Every chapter will develop multi-descriptional physicalism or defend it from objections. In chapter 1, I will propose a new conceptual reductive account that conceptually reduces higher-level entities to physical entities. This conceptual (...) reductive account combines resources from Heil’s truthmaker theory and either a priori physicalism or a posteriori physicalism. In chapter 2, I apply this conceptual reductive account to various debates. Physicalism, the multiple-realisability argument, the prototype theory of concepts, and truthmaker explanations will be discussed. In chapter 3, I will argue that a major aim of metaphysics should be to discover which entities are fundamental and explain why they suffice for the existence of derivative entities. In chapter 4, I will propose a new way to explain why sentences apparently about composite objects are true even though there are no composite objects. It combines resources from Cameron’s truthmaker theory and van Inwagen’s paraphrase strategy. In chapter 5, I will argue that the intuition that the mind and the body are very different does not show that the mind is distinct from the body. This intuition can be explained away by mentioning our dispositions to give non-physical explanations when we are ignorant of physical facts. In chapter 6, I will examine two arguments for the existence of a metaphysically independent level, and I will argue that only a modified version of one of them succeeds. I will argue that methodological principles support the view that there is a metaphysically independent level. (shrink)

The paper proposes a new technique for dealing with multi-attribute decision making problems through an extended TOPSIS method under neutrosophic cubic environment. Neutrosophic cubic set is the generalized form of cubic set and is the hybridization of a neutrosophic set with an interval neutrosophic set. In this study, we have defined some operation rules for neutrosophic cubic sets and proposed the Euclidean distance between neutrosophic cubic sets. In the decision making situation, the rating of alternatives with respect to (...) some predefined attributes are presented in terms of neutrosophic cubic information where weights of the attributes are completely unknown. In the selection process, neutrosophic cubic positive and negative ideal solutions have been defined. An extended TOPSIS method is then proposed for ranking the alternatives and finally choosing the best one. Lastly, an illustrative example is solved to demonstrate the decision making procedure and effectiveness of the developed approach. (shrink)

This paper presents a framework for exploring the temporal and behavioral aspects of the responses of various involved parties that may lead to governmental intervention in situations involving exposure of the public to hazardous substances. The activities of key individuals are closely scrutinized. Relevance of the framework to agricultural and food concerns is also indicated. The exemplary case is the contamination of livestock in Michigan that began in 1973, but other cases are discussed that conform closely to the pattern described (...) by the framework. (shrink)

A hypothesis about sensorimotor integration (the λ model) is described and applied to movement control and kinesthesia. The central idea is that the nervous system organizes positional frames of reference for the sensorimotor apparatus and produces active movements by shifting the frames in terms of spatial coordinates. Kinematic and electromyographic patterns are not programmed, but emerge from the dynamic interaction among the system s components, including external forces within the designated frame of reference. Motoneuronal threshold properties and proprioceptive inputs to (...) motoneurons may be cardinal components of the physiological mechanism that produces positional frames of reference. The hypothesis that intentional movements are produced by shifting the frame of reference is extended to multi-muscle and multi-degrees-of-freedom systems with a solution of the redundancy problem that allows the control of a joint alone or in combination with other joints to produce any desired limb configuration and movement trajectory. The model also implies that for each motor behavior, the nervous system uses a strategy that minimizes the number of changeable control variables and keeps the parameters of these changes invariant. Examples are provided of simulated kinematic and electromyographic signals from single- and multi-joint arm movements produced by suggested patterns of control variables. Empirical support is provided and additional tests of the model are suggested. The model is contrasted with others based on the ideas of programming of motoneuronal activity, muscle forces, stiffness, or movement kinematics. (shrink)

Two types of formal models - landscape search tasks and two-armed bandit models - are often used to study the effects that various social factors have on epistemic performance. I argue that they can be understood within a single framework. In this unified framework, I develop a model that may be used to understand the effects of functional and demographic diversity and their interaction. Using the unified model, I find that the benefit of demographic diversity is most pronounced (...) in a functionally homogeneous group, and decreases with the increase of functional diversity. (shrink)

This article attempts to study cost minimizing multi-objective fractional solid transportation problem with fuzzy cost coefficients c ˜ i j k r {\tilde{c}}_{ijk}^{r}, fuzzy supply quantities a ˜ i {\tilde{a}}_{i}, fuzzy demands b ˜ j {\tilde{b}}_{j}, and/or fuzzy conveyances e ˜ k {\tilde{e}}_{k}. The fuzzy efficient concept is introduced in which the crisp efficient solution is extended. A necessary and sufficient condition for the solution is established. Fuzzy geometric programming approach is applied to solve the crisp problem by defining (...) membership function so as to obtain the optimal compromise solution of a multi-objective two-stage problem. A linear membership function for the objective function is defined. The stability set of the first kind is defined and determined. A numerical example is given for illustration and to check the validity of the proposed approach. (shrink)

One of the major problems that artificial intelligence needs to tackle is the combination of different and potentially conflicting sources of information. Examples are multi-sensor fusion, database integration and expert systems development. In this paper we are interested in the aggregation of propositional logic-based information, a problem recently addressed in the literature on information fusion. It has applications in multi-agent systems that aim at aggregating the distributed agent-based knowledge into an (ideally) unique set of propositions. We consider (...) a group of autonomous agents who individually hold a logically consistent set of propositions. Each set of propositions represents an agent’s beliefs on issues on which the group has to make a collective decision. To make the collective decision, several aggregation procedures have been proposed in the literature. Assuming that all propositions in question are factually right or wrong, we ask how good belief fusion is as a truth tracker. Will it single out the true set of propositions? And how does information fusion compare with other aggregation procedures? We address these questions in a probabilistic framework and show that information fusion does especially well for agents with a middling competence of hitting the truth of an individual proposition. (shrink)

This paper proposes a Multi-Agent based Particle Swarm Optimization (PSO) Framework for the Traveling salesman problem (MAPSOFT). The framework is a deployment of the recently proposed intelligent multi-agent based PSO model by the authors. MAPSOFT is made up of groups of agents that interact with one another in a coordinated search effort within their environment and the solution space. A discrete version of the original multi-agent model is presented and applied to the Travelling Salesman Problem. Based on (...) the simulation results obtained, it was observed that agents retrospectively decide on their next moves based on consistent better fitness values obtained from present and prospective neighborhoods, and by reflecting back to previous behaviors and sticking to historically better results. These overall attributes help enhance the conventional PSO by providing more intelligence and autonomy within the swarm and thus contributed to the emergence of good results for the studied problem. (shrink)