Understanding Animal Intelligence: Practical Behavior Theory for Biology, Psychology, and Cognitive Science
Autor Stefano Ghirlanda, Magnus Enquisten Limba Engleză Paperback – oct 2025
This book summarizes and analyzes the framework of animal intelligence, focusing on decision-making, memory retrieval, associate learning, training, and more. It assesses both evolutionary and environmental factors that can influence an animal’s cognition and subsequent behavior. It demonstrates how learning can be reconciled with genetic predispositions that orient behavior toward adaptive outcomes. This book also provides a new understanding of motivational states and how these are used to fulfill different goals at different times, such as seeking food and water.
Understanding Animal Intelligence: Practical Behavior Theory for Biology, Psychology, and Cognitive Science is an important reference and course reading in animal behavior, animal physiology, and ethology.
- Features similarly structured chapters for easy reading and referencing
- Includes steps to understand, apply, and analyze math and coding, as well as exercises for readers to practice independently
- Uses the R statistical environment and LearningSimulator.org for real-world modelling
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Specificații
ISBN-13: 9780443157301
ISBN-10: 0443157308
Pagini: 400
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
ISBN-10: 0443157308
Pagini: 400
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
Cuprins
Part I: Fundamental questions
1. What does it mean to understand animal intelligence?
2. Different purposes of mechanistic, developmental, and evolutionary explanations
3. Describing behavior – responses to stimuli, individual history, evolutionary history
4. Modeling animal intelligence – decision-making, learning, and evolution
Part II: Decision-making
5. Using available information to select the best action – external stimuli, memories, and motivational states
6. Evaluation of current stimuli – perception, generalization, relationship with deep learning
7. Memory retrieval – selecting which information to use
8. Motivational systems – selecting which goal to pursue
9. Inborn contributions to decision-making strategies
Part III: Learning and development
10. Associative learning – a modern perspective on reinforcement learning
11. Specialized memory systems – purposes and algorithms
12. Genetic guidance of learning
13. Learned information
14. Maturation – changing behavioral mechanisms with age and experience
15. Training – teaching animals beyond their inherent scope
Part IV: Evolution of behavior
16. Evolution’s effect on learning and decision-making
17. Innate value landscapes
18. Co-evolution of animal intelligence with environmental demands
1. What does it mean to understand animal intelligence?
2. Different purposes of mechanistic, developmental, and evolutionary explanations
3. Describing behavior – responses to stimuli, individual history, evolutionary history
4. Modeling animal intelligence – decision-making, learning, and evolution
Part II: Decision-making
5. Using available information to select the best action – external stimuli, memories, and motivational states
6. Evaluation of current stimuli – perception, generalization, relationship with deep learning
7. Memory retrieval – selecting which information to use
8. Motivational systems – selecting which goal to pursue
9. Inborn contributions to decision-making strategies
Part III: Learning and development
10. Associative learning – a modern perspective on reinforcement learning
11. Specialized memory systems – purposes and algorithms
12. Genetic guidance of learning
13. Learned information
14. Maturation – changing behavioral mechanisms with age and experience
15. Training – teaching animals beyond their inherent scope
Part IV: Evolution of behavior
16. Evolution’s effect on learning and decision-making
17. Innate value landscapes
18. Co-evolution of animal intelligence with environmental demands