Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior (...) work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial—but not temporal—variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing. (shrink)

The projection pattern of the existential/uniqueness presupposition of a wh-complement varies depending on the predicate that embeds it. This variation poses problems for existing accounts that treat the presupposition as a semantic contribution of an operator merging with the wh-complement or of the embedding predicate. I propose that the problems can be solved if the existential/uniqueness presupposition is contributed by the propositions corresponding to the answers of the embedded question, under the Hamblin/Karttunen semantics for questions.

秋成とともに同時代を生き、上方和学の展開を担った国学者の言説、学芸、伝記、学統等を総合的に解明することで、近世中後期における上方和学の実態を多角的に把握することを目指す。.

The conflict between Platonic realism and Constructivism marks a watershed in philosophy of mathematics. Among other things, the controversy over the Axiom of Choice is typical of the conflict. Platonists accept the Axiom of Choice, which allows a set consisting of the members resulting from infinitely many arbitrary choices, while Constructivists reject the Axiom of Choice and confine themselves to sets consisting of effectively specifiable members. Indeed there are seemingly unpleasant consequences of the Axiom of Choice. The non-constructive nature of (...) the Axiom of Choice leads to the existence of non-Lebesgue measurable sets, which in turn yields the Banach-Tarski Paradox. But the Banach-Tarski Paradox is so called in the sense that it is a counter-intuitive theorem. To corroborate my view that mathematical truths are of non-constructive nature, I shall draw upon Gödel’s Incompleteness Theorems. This also shows the limitations inherent in formal methods. Indeed the Löwenheim-Skolem Theorem and the Skolem Paradox seem to pose a threat to Platonists. In this light, Quine/Putnam’s arguments come to take on a clear meaning. According to the model-theoretic arguments, the Axiom of Choice depends for its truth-value upon the model in which it is placed. In my view, however, this is another limitation inherent in formal methods, not a defect for Platonists. To see this, we shall examine how mathematical models have been developed in the actual practice of mathematics. I argue that most mathematicians accept the Axiom of Choice because the existence of non-Lebesgue measurable sets and the Well-Ordering of reals open the possibility of more fruitful mathematics. Finally, after responding to Benacerraf’s challenge to Platonism, I conclude that in mathematics, as distinct from natural sciences, there is a close connection between essence and existence. Actual mathematical theories are the parts of the maximally logically consistent theory that describes mathematical reality. (shrink)

Profit Sharing is one of the reinforcement learning methods. An agent, as a learner, selects an action with a state-action value and receives rewards when it reaches a goal state. Then it distributes receiving rewards to state-action values. This paper discusses how to set the initial value of a state-action value. A distribution function ƒ( x ) is called as the reinforcement function. On Profit Sharing, an agent learns a policy by distributing rewards with the reinforcement function. On Markov Decision (...) Processes (MDPs), the reinforcement function ƒ( x ) = 1/ L x is useful, and on Partially Observable Markov Decision Processes (POMDPs), ƒ( x ) = 1/ L w is useful, where L is the sufficient number of rules at each state, and W is the length of an episode. If episodes are always long, the value of the reinforcement function is little. So the differences of rule values become little, and the agent learns little by using the roulette selection as an action selection. This problem is called as Learning Speed Problem. If the value of the reinforcement function for an action is very higher than its state-action value, an agent will not select other action. There is a problem when its action is not a optimal action. This problem is called as Past Experiences Problem. This paper shows that both Learning Speed Problem and Past Experiences Problem are caused by the bad setting between the initial values of a state-action values and the function values of a reinforcement function. We propose how to set the initial values of a state-action values at each state. The experiment shows that an agent can learn correctly even if the length of episode is large. And shows the effectiveness on both MDPs and POMDPs. Our proposed method focuses on the initialization of state-action values and does not limit reinforcement functions. So it can apply to any reinforcement function. (shrink)

In this paper, we consider profit sharing that is one of the reinforcement learning methods. An agent learns a candidate solution of a problem from the reward that is received from the environment if and only if it reaches the destination state. A function that distributes the received reward to each action of the candidate solution is called the reinforcement function. On this learning system, the agent can reinforce the set of selected actions when it gets the reward. And the (...) agent should not reinforce the detour actions. First, we will propose a new constraint equation about reinforcement functions to distribute the reinforcement values on the non-detour actions. If we use the reinforcement function to satisfy the constraint equation, the agent can select the non-detour actions directing to the destination state. Next, it is shown that the reinforcement function can be constant after learning process to suppress the selection of detour actions. Lastly, in computer simulations for maze problems, we show that the learning performance of agents does not depend on the size of environment. (shrink)

Reconsideration-proofness is a solution concept proposed by Kocherlakota :33–54, 1996) for infinite horizon single-player problems in which time inconsistency is important. Kocherlakota’s definition has a limitation: it is not applicable to environments with state variables. The limitation is important because many time-inconsistent problems have state variables. This paper displays a natural generalization of reconsideration-proofness to environments with state variables, and shows that it leads to nonexistence in three examples. Such nonexistence contrasts with the general existence theorem obtained in environments without (...) state variables in Kocherlakota. In the first two examples, existence can be recovered with a modification in the solution concept. In the last example, nonexistence occurs even with the modified solution concept. Insights about further research are derived from these nonexistence results. (shrink)

Clause-embedding predicates come in three major varieties: responsive predicates are compatible with both declarative and interrogative complements; rogative predicates are only compatible with interrogative complements; and anti-rogative predicates are only compatible with declarative complements. It has been suggested that these selectional properties are at least partly semantic in nature. In particular, it has been proposed that the anti-rogativity of neg-raising predicates like believe comes from the triviality in meaning that would arise with interrogative complements. This paper puts forward a similar (...) semantic explanation for non-veridical preferential predicates such as hope, which are anti-rogative, unlike their veridical counterparts such as be happy, which are responsive. (shrink)

We recently described a novel form of stress‐associated bidirectional plasticity at GABA synapses onto hypothalamic parvocellular neuroendocrine cells (PNCs), the apex of the hypothalamus‐pituitary‐adrenal axis. This plasticity may contribute to neuroendocrine adaptation. However, this GABA synapse plasticity likely does not translate into a simple more and less of inhibition because the ionic driving force for Cl−, the primary charge carrier for GABAA receptors, is dynamic. Specifically, stress impairs a Cl− extrusion mechanism in PNCs. This not only renders the steady‐state GABA (...) response less hyperpolarizing but also makes PNCs susceptible to the activity‐dependent accumulation of Cl−. Accordingly, GABA synapse plasticity impacts both the robustness of GABA voltage response and dynamic Cl− loading, imposing nonlinear influences on PNC excitability during circuit activities. This theoretical consideration predicts roles for GABA transmission far more versatile than canonical inhibition. We propose potential impacts of GABA synapse plasticity on the experience‐dependent fine‐tuning of neuroendocrine stress responses. (shrink)

Objective:This study aimed to investigate the effect of robot-assisted gait training therapy combined with non-invasive brain stimulation on lower limb function in patients with stroke and spinal cord injury.Data sourcesPubMed, Cochrane Central Register of Controlled Trials, Ovid MEDLINE, and Web of Science were searched.Study selectionRandomized controlled trials published as of 3 March 2021. RCTs evaluating RAGT combined with NIBS, such as transcranial direct current stimulation and repetitive transcranial magnetic stimulation, for lower limb function and activities in patients with stroke and (...) SCI were included.Data extractionTwo reviewers independently screened the records, extracted the data, and assessed the risk of bias.Data synthesisA meta-analysis of five studies and risk of bias were conducted. Pooled estimates demonstrated that RAGT combined with NIBS significantly improved lower limb function [standardized mean difference = 0.52; 95% confidence interval = 0.06–0.99] but not lower limb activities. Subgroup analyses also failed to find a greater improvement in lower limb function of RAGT with tDCS compared to sham stimulation. No significant differences between participant characteristics or types of NIBS were observed.ConclusionThis meta-analysis demonstrated that RAGT therapy in combination with NIBS was effective in patients with stroke and SCI. However, a greater improvement in lower limb function and activities were not observed using RAGT with tDCS compared to sham stimulation. (shrink)

As the internet becomes the basic resource of information, not only texts but images retrieval systems have been appeared. However, many of those supply only a list of images, so we have to seek the expecting images one by one. Although, image labeling is one of the solutions of such a problem, various words are labeled to an image if the words are extracted from only one Web page. Therefore, this paper proposes an image clustering system that labels images by (...) words related to a search keyword. This relationships are measured by Web pages in WWW. By the experimental results, users were enabled to find the intended images more faster than the ordinal image search system. (shrink)

Android robots capable of emotional interactions with humans have considerable potential for application to research. While several studies developed androids that can exhibit human-like emotional facial expressions, few have empirically validated androids’ facial expressions. To investigate this issue, we developed an android head called Nikola based on human psychology and conducted three studies to test the validity of its facial expressions. In Study 1, Nikola produced single facial actions, which were evaluated in accordance with the Facial Action Coding System. The (...) results showed that 17 action units were appropriately produced. In Study 2, Nikola produced the prototypical facial expressions for six basic emotions, and naïve participants labeled photographs of the expressions. The recognition accuracy of all emotions was higher than chance level. In Study 3, Nikola produced dynamic facial expressions for six basic emotions at four different speeds, and naïve participants evaluated the naturalness of the speed of each expression. The effect of speed differed across emotions, as in previous studies of human expressions. These data validate the spatial and temporal patterns of Nikola’s emotional facial expressions, and suggest that it may be useful for future psychological studies and real-life applications. (shrink)

Le présent article a pour but d’expliciter le caractère d’existence de la signification du point de vue de la sémantique. Il est ici prouvé que la signification ne peut être en tant que telle ni psychique, ni physique, ni même métaphysique, ce qui nous pousse à nous opposer à toutes les vues qui ont eu cours sur la signification. Car la signification consiste, en soi et pour soi, dans le rapport quadripartite...