Animal Learning Research Articles

An algorithm that excavates suboptimal states and improves Q-learning

Abstract Reinforcement learning is inspired by the trial-and-error method in animal learning, where the reward values obtained from the interaction of the agent with the environment are used as feedback signals to train the agent. Reinforcement learning has attracted extensive attention in recent years. It is mainly used to solve sequential decision-making problems and has been applied to various aspects of life, such as autonomous driving, game gaming, and robotics. Exploration and exploitation are the main characteristics that distinguish reinforcement learning methods from other learning methods. Reinforcement learning methods need reward optimization algorithms to better balance exploration and exploitation. Aiming at the problems of unbalanced exploration and a large number of repeated explorations in the Q-learning algorithm in the MDP environment, an algorithm that excavates suboptimal states and improves Q-learning was proposed. It adopts the exploration idea of ‘exploring the potential of the second-best’, and explores the state with suboptimal state value, and calculates the exploration probability value according to the distance between the current state and the goal state. The larger the distance, the higher the exploration demand of the agent. In addition, only the immediate reward and the maximum action value of the next state are needed to calculate the Q value. Through the simulation experiments in two different MDP environments, The frozenLake8x8 environment and the CliffWalking environment, the results verify that the proposed algorithm obtains the highest average cumulative reward and the least total time consumption.

Guiding Educational Designers in partnership with Gen AI

The journey to becoming an Educational Designer (ED) can be daunting – creating many feelings, the most popular of those being imposter syndrome (Pingo et al., 2024). These feelings, although mostly not validated, create subjective hindrances to participating in and contributing to the field (Sage & Sankey, 2021). This poster explores a partnership with Generative Artificial Intelligence (GenAI) as a way to provide a scaffold for anyone new to the field. To do this, one of the author’s own journey to becoming an ED is used as an example to create a blueprint of how to navigate new terrain. By partnering with GenAI (i.e., ChatGPT), the authors use an emic lens to survey a journey through three distinct eras (Beals et al., 2020). These eras evolved from the intersection of professional, personal and environmental influences and captures a newcomers’ introduction to the field situated in the professional space of higher education. The narrated data captured via subjective reflections of lived experiences, are transcribed and then partnered with ChatGPT to be thematically analysed. The authors then engage an etic lens to objectively use media (e.g., newspapers, magazines, videos, etc.) to illustrate the journey using the themes to gain more meaning towards personal agency for the profession (Méndez, 2013). This autoethnography creates great insight into how a newcomer can uniquely and individually create a self-serving map to increase a sense of belonging by partnering with a non-human intelligence tool. Using ChatGPT reduces the feelings of being judged – the feelings associated with imposter syndrome - yet creating a path that may not be seen without such an intervention. By leveraging human-influenced algorithms almost like a mentor, GenAI can identify patterns and themes in the narratives that might be overlooked by human analysis – a symbiosis of autoethnography and GenAI (McNally et al., 2022). Adopting autoethnography as a method to navigate professional, social and cultural terrains, via an emic and etic lens of lived experiences, personal vignettes and introspection provide the qualitative inputs to be examined and interpreted (Beals et al., 2020; Méndez, 2013). The second step in this research involves the use of GenAI as a tool for analysing and interpreting this self-reflective data (Boulus-Rødje et al., 2024). This research strategy holds relevance for educational designers and the wider community of third-space professionals, particularly those who may be new to the field or navigating a career transition. It will demonstrate the potential of GenAI as a tool for interpreting and applying autoethnographic data in a practical, actionable way. The insights generated could inform the development of GenAI-driven tools and resources that support educational designers to develop their professional identity. By highlighting the value of transferable skills and experiences through a resulting blueprint, the mapping of the imposter-syndrome-like feelings among third space professionals could be mitigated. This will allow for transformations of self-perceptions to aid in the recognition of one’s unique contributions to confidently engage with the profession and the field.

Leveraging how animals learn in conservation science: Behavioral responses of reintroduced bison to management interventions

AbstractReintroduction programs have increased amid unprecedented biodiversity loss, yet the success of these programs lag. A prominent reason for program failure is dispersal beyond the planned range of the population. Management techniques, such as hazing, can be used to prevent movement beyond set boundaries, but to be effective long‐term, the animals must learn to avoid the areas where they are hazed. Although concepts of animal learning have been used to improve reintroduction programs, learning is not often explicitly tested or used as an indicator of program success. We used a conservation behavior framework to evaluate how a range of management techniques influenced learning in a reintroduced population of bison in Banff National Park, Canada. We hypothesized exposure to stronger negative stimuli would enhance learning, leading to more pronounced behavioral responses. Specifically, we tested the degree to which management actions (i.e., drift fence encounters, foot, horseback, helicopter, and combined hazing) elicited behavioral responses and how they facilitated learning. Consistent with our predictions, drift fence interactions and foot and horseback hazing elicited fewer behavioral responses of a smaller magnitude than helicopter hazing or combined methods, suggesting these techniques cause less disturbance to the bison. Bison continually returned to locations where they encountered management actions that caused the least disturbance, demonstrating a lack of associative learning. Bison appeared to form negative associations with locations where they were hazed via helicopter or combined methods, however, and rarely returned to these locations. Evaluating management techniques is essential for improving conservation success. We demonstrate that by bridging the fields of conservation biology and animal learning, we can understand how management techniques influence learning and behavior thereby facilitating effective conservation plans that incorporate disruption levels of the animals, financial costs, and overall effectiveness. Effective conservation plans, in turn, improve our likelihood of successfully managing and recovering species.

LEGAL CONSEQUENCES: DISSOLUTION OF MARRIAGE DUE TO DIVORCE SUITS FROM DIFFERENT RELIGIONS (Study Decision Number: 55/Pdt.G/2022/PN.Tjk)

Marriage is the behavior of creatures created by God Almighty so that life in the natural world can reproduce. Because humans are intelligent creatures, marriage is one of the orderly and sacred cultures that follows the development of human culture in the development of social life. Law Number 1 of 1974 concerning Marriage, namely regarding the maintenance of children, joint assets and maintenance/expenses for the wife and children. The responsibility of parents who have divorced for the support of minor children is that children who are not yet mumayyiz (12 years old) have the right to receive hadhanah from their mother, unless the mother dies, then her position is replaced by women in a straight line up from the mother. , women in a straight line upwards from the father, sister of the child in question. Implementation of the Divorce Process in the District Court Study Decision Number: 55/Pdt.G/2022/PN. Tjk is the same as the process is not much different from How to file a divorce suit by a Muslim couple. Non-Muslim couples are required to file a divorce suit at the district court, so that their divorce is valid in the eyes of the law of the nation and state. With supporting reasons for the divorce lawsuit, the divorce lawsuit will be granted by the court.

Noisy nests: Early-life noise exposure impacts songbird fitness.

Recent findings indicate that noise pollution - presented in the absence of other variables - has both immediate-term impacts on young birds' developmental rates and physiology as well as long-term effects on adult telomere length and reproductive success. This work highlights yet another set of negative impacts caused by anthropogenic noise, and suggests that the dramatic fitness consequences observed likely have implications for the evolution of learning and behavior in animals living in noisy environments.

Intelligence: Natural, artificial, or what?

We consider the competing attributes of natural intelligence (NI) and artificial intelligence (AI). Attention is paid to conceptual, theoretical, stylistic and structural aspects of both, and non-human intelligence. Intelligence is related to information processing and current views of physical structuring. Means of distinguishing between NI and AI are noted, and neural and digital structures are described. Pribram's bi-computational neural networks are introduced, and high-level Pribram computation is discussed. We describe the hierarchical Aquarium scheme, along with an AI implementation, and conclude with a proposition for future quantum-based artificial intelligence.

Meating of the minds: Who denies animal mind in response to the meat paradox?

Most people abhor animal cruelty but choose to eat meat. To resolve feelings of conflict associated with this so-called “meat paradox”, meat-eaters appear to downplay the capacity of animals to think and feel. However, the strength of animal mind denial seems likely to vary between individuals—according to one’s concern for animal welfare or enjoyment of meat, for instance. Across two pre-registered studies (S1: N = 355, S2: N = 251), we examined personality traits, attitudes, and beliefs that may predict the strength of animal mind denial in relation to the meat paradox. Results suggest that those lower in openness/intellect or emotion regulation ability, or higher in meat-commitment, deny animal mind more strongly when reminded of the link between meat eating and animal suffering. We discuss the degree to which these findings align with dissonance-based explanations for animal mind-denial in response to the meat-paradox.

Why might animals remember? A functional framework for episodic memory research in comparative psychology.

One of Clayton's major contributions to our understanding of animal minds has been her work on episodic-like memory. A central reason for the success of this work was its focus on ecological validity: rather than looking for episodic memory for arbitrary stimuli in artificial contexts, focussing on contexts in which episodic memory would serve a biological function such as food caching. This review aims to deepen this insight by surveying the numerous functions that have been proposed for episodic memory, articulating a philosophically grounded framework for understanding what exactly functions are, and drawing on these to make suggestions for future directions in the comparative cognitive psychology of episodic memory. Our review suggests four key insights. First, episodic memory may have more than one function and may have different functions in different species. Second, cross-disciplinary work is key to developing a functional account of episodic memory. Third, there is scope for further theoretical elaboration of proposals relating episodic memory to food caching and, in particular, future-oriented cognition. Finally, learning-related functions suggested by AI (artificial intelligence)-based models are a fruitful avenue for future behavioural research.

Social exploration: How and why people seek new connections.

Just as animals forage for food, humans forage for social connections. People often face a decision between exploring new relationships versus deepening existing ones. This trade-off, known in optimal foraging theory as the exploration-exploitation trade-off, is featured prominently in other disciplines such as animal foraging, learning, and organizational behavior. Many of the framework's principles can be applied to humans' choices about their social resources, which we call social exploration/exploitation. Using known principles in the domain of social exploration/exploitation can help social psychologists better understand how and why people choose their relationships, which ultimately affect their health and well-being. In this article, we discuss the costs and benefits of social exploration and social exploitation. We then synthesize known person- and situation-level predictors of social decision making, reframing them in the language of the explore-exploit trade-off. We propose that people explore more when they find it more rewarding and less costly, and when the environment has many opportunities to do so. We conclude by discussing hypotheses generated by applying optimal foraging theory to social decision making. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

#Dolphins: communication and engagement in marine mammal tourism attractions

ABSTRACT This paper delves into the ethical dimensions and public perceptions surrounding dolphin tourism, both seeing them in the wild and in the marine park. Using a comprehensive analysis of social media data over seven years, we focus on dolphins as a central element of marine mammal tourism, investigating how digital narratives shape tourist attitudes and behaviours towards these intelligent creatures. Informed by a multi-method data analysis approach, this study reveals an “echo chamber” effect in social media, perpetuating selective exposure to information that aligns with visitor motivations: hedonism, relevance and reverence. The theoretical contributions of this research extend the existing literature on wildlife tourism by offering a deeper understanding of how public sentiments towards animals in tourism settings evolve and influence tourism practices. The finding underscores the need for informed, ethical communication strategies that consider the complex interplay of entertainment, education, and conservation in wildlife tourism.

A personal tribute to Frans De Waal (1948–2024), who inspired the philosophy of animal minds

A personal tribute to Frans De Waal (1948–2024), who inspired the philosophy of animal minds

A psychological mechanism for the development of anxiety.

Although numerous behavioral constructs have been proposed to account for anxiety disorders, how these disorders develop within an individual has been difficult to predict. In this perspective, I selectively review clinical and experimental evidence suggesting that avoidance (i.e., safety) behavior increases beliefs of threat or fear. The experimental evidence has been replicated numerous times, with different parameters, and shows that when human participants emit avoidance responses in the presence of a neutral stimulus, they later show heightened expectations of threat in the presence of the neutral stimulus. I interpret these findings as resulting from prediction errors as anticipated by the Rescorla-Wagner model, although other animal learning theories can also predict the phenomenon. I discuss some implications and offer a few novel predictions. The analysis presented here sheds light on a phenomenon of theoretical and clinical relevance which is accommodated by basic associative learning theory. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Space Alpha Particle Fluxes Towards the Earth Increase Human Mortality. Is It Possible an Intervention of Non-Human Intelligence?

In the present work, a dangerous phenomenon for mankind is described, increasing mortality, mainly from the most deadly diseases on the planet – circulatory diseases, in particular ischemic heart diseases. In the joint analysis of data from satellites in orbit around the Earth and from the health statistics sources EUROSTAT and US medical statistics, it became clear that, by some mechanism, flows of positively charged particles with high energy entering the Earth's orbit increase human mortality, mainly from diseases of the circulatory system, but also from diseases of many other organs and systems of the human body. The circulatory disease mortality increase as a result of said alpha radiation is by an average of 5% to 15% in a zone of maximum risk in the Northern Hemisphere, parallel to the equator and bounded by the parallels of 30° and 50° north latitude. A hypothetical mechanism based on observational evidence has been proposed, according to which this dangerous phenomenon is due to solar alpha particles of high energy sufficient to overcome the resistance of the atmosphere and reach the Earth's surface in a limited area of maximum death impact. The impact is most often short-lasting – for minutes, hours, or sometimes a few days. In the area with maximum risk, alpha particles have a detrimental effect on the human body. The area with maximum risk is limited in area and in time by two conditions 1. the path of the particles through the atmosphere to the Earth's surface is as short as possible (during the local culmination of the Sun, local noon) and 2. the direction of the incoming alpha particles coincides with the direction of the vector of geomagnetic induction at the point of maximum risk, where alpha particles are not affected by the deflecting force of the geomagnetic field. Such a coincidence between the culmination of the Sun, which changes during the year, and the direction of the geomagnetic induction vector, which is unchanged for a given point of observation, occurs twice a year for points with a geographical latitude of 30° – 50° N. Examples are given confirming the proposed mechanism of action. In the second part of the study, attention is paid to the nature of alpha particle streams reaching the Earth's orbit. In addition to those emitted by the Sun as a result of natural processes, there are also series of pulses lasting less than 5 minutes, with strict periodicity in the series day or week, with the same moment of registration of the pulses and coincidence of the pulses in the series by magnitude over extended time intervals, sometimes over the lifetime of the series from months to years. The alpha particles from each pulse in the series bombard the Earth's surface always in the same place. There are many such series, differing in time of recording and period, each of which is focused on a certain region of the Earth's surface. Such are, in particular, the series of pulses affecting the territory of the USA, Europe, and Central Asia. There is statistical confirmation in the US health statistics that the series of pulses affecting the country cause an increase in the mortality of ischemic heart disease by up to 5%. The lack of free access to detailed statistics on the cases of death in the other countries affected by the phenomenon does not allow a conclusion of the impact of the series of pulses of alpha particles on the health of their inhabitants. The strange characteristics of the mentioned series of pulses of alpha particles do not exclude the hypothesis that they are artificially generated from a non-human mind. The level of technological development of human civilization does not imply the possibility for it to generate such large-scale processes as the series of pulses of alpha particles, i.e. the highly developed non-human mind that generates them has nothing to do with human civilization. The series of pulses may be navigational signals causing unwitting casualties to humanity, but they may also be a form of murderous contact with a higher civilization that we have long sought, expecting only benefits after its realization, not suspecting that we live in this nightmarish contact indefinitely.

Attachment as the Catalyst for the Attribution of Complex Cognition and Emotion to Companion Cats.

Companion cat caregivers ascribe complex emotions and cognitions to their cats, and these attributions are greater with a stronger attachment to their animals. We compared attributions of emotional and cognitive complexity to cats in cat caregivers and non-caregivers. We measured attitudes toward animals, belief in animal minds, caregivers' strength of attachment, and attachment style with a particular companion cat in 448 university students, of whom 251 had owned a cat. We asked the extent to which respondents thought that cats were capable of expressing primary and secondary emotions and cognitive capabilities. Caregivers significantly differed from non-caregivers only in the attribution of primary emotions. Belief in animal minds predicted the attribution of secondary emotions and cognition. For caregivers only, avoidant attachment style was negatively associated with the attribution of primary emotions, whereas attachment strength was positively associated with the attribution of secondary emotions and cognition. These abilities may have greater discriminatory power as most respondents ascribe primary emotions to cats, perhaps for anthropomorphic reasons. Housing conditions (indoor and outdoor) were not associated with attributions, suggesting that bonds are more important than time spent together within the home in predicting the attribution of emotional and cognitive complexity in cats.

Artificial Intelligence-Entrepreneurship Future Research and Opportunities for New Business Model

Artificial Intelligence (AI) is a capability related to intelligent creatures in the form of artificial robots which are fully controlled by digital computers. The presence of Artificial Intelligence (AI) certainly changes the structure of human life which affects the effectiveness of human performance such as in the field of entrepreneurship. The main scope in artificial intelligence technology is gaining strategic advantage in digital business, human resources, market research, customer relations, accounting and finance, sales, marketing, and others. The investigation of this work is centered to understand more about Artificial Intelligence, opportunities for using Artificial Intelligence for entrepreneurship, perspectives that support AI technology as part of the new model of business, perspectives against the development of artificial intelligence, as well as future opportunities from artificial intelligence technology.

Studying Great Apes and Cultural Diversity To Understand the Human Mind

Psychologists want to understand how the human mind is extraordinary among animal minds and where the unique aspects of human minds and behaviors come from. To build scientific understanding of human minds, we must study the wide range of humans across cultures, to know what all humans have in common and which aspects of human minds are diverse. However, this is not enough—studying humans across cultures tells us how humans think and act, not how they are unique among animals. To understand how humans are similar and different from other animals, we must study other animals too, especially our close primate relatives, the great apes, who have minds that are similar to ours in many, but not all, ways. So, to understand human minds and behaviors, researchers should study humans and non-humans at a scale that allows us to explore the origins of the similarities and differences of minds and behaviors across our world today.

Abracadabra! How magic can help us understand animal minds

Abracadabra! How magic can help us understand animal minds

Heterogeneity in strategy use during arbitration between experiential and observational learning

To navigate our complex social world, it is crucial to deploy multiple learning strategies, such as learning from directly experiencing action outcomes or from observing other people’s behavior. Despite the prevalence of experiential and observational learning in humans and other social animals, it remains unclear how people favor one strategy over the other depending on the environment, and how individuals vary in their strategy use. Here, we describe an arbitration mechanism in which the prediction errors associated with each learning strategy influence their weight over behavior. We designed an online behavioral task to test our computational model, and found that while a substantial proportion of participants relied on the proposed arbitration mechanism, there was some meaningful heterogeneity in how people solved this task. Four other groups were identified: those who used a fixed mixture between the two strategies, those who relied on a single strategy and non-learners with irrelevant strategies. Furthermore, groups were found to differ on key behavioral signatures, and on transdiagnostic symptom dimensions, in particular autism traits and anxiety. Together, these results demonstrate how large heterogeneous datasets and computational methods can be leveraged to better characterize individual differences.

AN IN-DEPTH EXPLORATION OF ARTIFICIAL INTELLIGENCE IN THE CONTEXT OF CONTEMPORARY DATA CHALLENGES; DIFFERENCES BETWEEN HUMAN AND MACHINE LEARNING

Machine learning and artificial intelligence produce algorithms that appear to be able to make "intelligent" decisions similar to those of humans but function differently from human thinking. To make decisions based on machine suggestions, humans should be able to understand the background of these suggestions. However, since humans are oriented to understand human intelligence, it is not yet fully clear whether humans can truly understand the "thinking" generated by machine learning, or whether they merely transfer human-like cognitive processes to machines. In addition, media representations of artificial intelligence show higher capabilities and greater human likeness than they currently have. In our daily lives, we increasingly encounter assistance systems that are designed to facilitate human tasks and decisions based on intelligent algorithms. These algorithms are predominantly based on machine learning technologies, which make it possible to discover previously unknown correlations and patterns by analyzing large amounts of data. One example is the machine analysis of thousands of X-ray images of sick and healthy people. This requires identifying the patterns by which images labeled as "healthy" can be distinguished from those labeled as "sick" and to find an algorithm that identifies the latter. In the meantime, "trained" algorithms created in this way are used in various fields of application, not only for medical diagnoses but also in the pre-selection of applicants for a job advertisement or in communication with the help of voice assistants. These voice assistants are enabled by intelligent algorithms to offer internet services through short commands. Harald Lesch, referring to his book Unpredictable, written together with Thomas Schwarz, says the development of artificial intelligence can be compared to bringing aliens to Earth. With machine learning, a previously unknown form of non-human intelligence has been created. This chapter discusses whether forms of artificial intelligence, as they are currently being publicly discussed, differ substantially from human thinking. Furthermore, it will be discussed to what extent humans can comprehend the functioning of artificial intelligence that has been created through machine learning when interacting with them. Finally, the risks and opportunities will be weighed and discussed..

Daily quetiapine after severe TBI improves learning and memory.

Traumatic brain injury (TBI) induces cognitive deficits driven by neuroinflammation and cerebral edema. The commonly used atypical antipsychotic, quetiapine (QTP), has been recently shown to improve post-TBI outcomes. We hypothesized that QTP would thereby improve animal learning and memory 2 weeks after severe TBI. CD1 male mice (n = 35) underwent severe TBI (controlled cortical impact, injury, I) or sham craniotomy (S), followed by BID saline (P, placebo) or QTP (10 or 20 mg/kg, IP) for 2 weeks. Animals underwent Morris Water Maze (MWM) exercises to gauge spatial learning and memory. The distance and time required for swimming animals to reach the platform area (Zone 5, Z5) located in quadrant 1 (Zone 1, Z1) was calculated from digital video recordings analyzed using Ethovision software. Animal bodyweights were recorded daily and on day 14, injured cerebral hemispheres were procured for edema determination (wet-to-dry ratio). Intergroup differences were evaluated with ANOVA/Bonferroni correction (p < 0.05). On day 14, animal weight loss recovery was lowest in I + P compared to I + QTP20 and I + QTP10 (p ≤ 0.01 for either). Cerebral edema was greatest in I + P, and only significantly decreased in I + QTP20 (p < 0.05). Both QTP doses similarly improved spatial learning by significantly reducing latency time and travel distance to target zones (p < 0.05). In probe memory trials, only I + QTP20 and not I + QTP10 significantly favored animal reaching or crossing into target zones (p < 0.05). Post-TBI QTP reduces brain edema and improves spatial learning and memory with a potential dose dependence impact benefiting memory up to 14 days. These data suggest an unanticipated QTP benefit following brain injury that should be specifically explored.