Business Ethics

An investigation of ethical questions that arise in the world of business, including the business of the academy; and scrutiny of the moral principles that may enable people to cope successfully with these questions.

Philosophy & Gender

This course examines philosophical conceptions of sex, gender, and sexuality in the context of contemporary ethical questions. In what ways are our conceptions of gender created and reinforced through cultural and social norms? How do assumptions about sex, gender, and sexuality shape and potentially limit research in natural and social sciences? In what ways are feminist and multiculturalist goals potentially at odds? Is sex and sexuality the public’s business? How do gender identities intersect with other identities?

Animal Minds & Ethics

Over the past few decades there has been an explosion of research on animal consciousness. This class examines three interrelated issues: (i) questions of animal consciousness, (ii) issues related to the study of animal consciousness, and (iii) how current understandings of animal consciousness should impact our treatment of animals.

Intro to Epistemology

What is knowledge? How is one justified in what they believe or know? How does one reconcile this with who they are as thinkers and their lived experience? This course is designed to acquaint students with some potential answers to these questions through a survey of contemporary analytic, virtue/vice, social, and feminist epistemology. The course examines theories of knowledge and justification alongside social and political contexts, and considers how these factors impact the ways people acquire and share knowledge individually and collectively.

Jacqueline Victoria White

Submitted by admin on
Primary Title:  
Research Fellow
Institution:  
UMASS Amherst
Department:  
Civil & Environmental Engineering
Email Address:  
jvwhite@umass.edu
Office Building:  
Marston Hall

Yelena Bernadskaya

Submitted by admin on
Primary Title:  
Assistant Professor
Institution:  
UMASS Amherst
Department:  
Biology
Email Address:  
ybernadskaya@umass.edu

Midenson Mathurin

Submitted by admin on
Primary Title:  
Custodian
Institution:  
Hampshire College
Department:  
Physical Plant
Email Address:  
midmPP@hampshire.edu
Office Building:  
Physical Plant

FYS-Learning/Trial & Error

How can we teach machines to learn on their own? In this seminar, we will explore this question by examining how computers can learn from experience?just like humans and animals do. One way they do this is through reinforcement learning, a technique used to solve a wide range of problems, from training self-driving cars to teaching robots to clean kitchens. You will learn why this method of learning is both powerful and sometimes challenging, how to identify real-world problems that can be addressed in this way, and how to frame such problems so that a computer can learn to solve them.

FYS-Learning/Trial & Error

How can we teach machines to learn on their own? In this seminar, we will explore this question by examining how computers can learn from experience?just like humans and animals do. One way they do this is through reinforcement learning, a technique used to solve a wide range of problems, from training self-driving cars to teaching robots to clean kitchens. You will learn why this method of learning is both powerful and sometimes challenging, how to identify real-world problems that can be addressed in this way, and how to frame such problems so that a computer can learn to solve them.

FYS-Learning/Trial & Error

How can we teach machines to learn on their own? In this seminar, we will explore this question by examining how computers can learn from experience?just like humans and animals do. One way they do this is through reinforcement learning, a technique used to solve a wide range of problems, from training self-driving cars to teaching robots to clean kitchens. You will learn why this method of learning is both powerful and sometimes challenging, how to identify real-world problems that can be addressed in this way, and how to frame such problems so that a computer can learn to solve them.
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