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Ashoka University’s undergraduate course curriculum is taught across three semesters: Spring, Summer and Monsoon (Fall). Courses are broadly divided into three categories – Foundation Courses (core curriculum), Major & Minor Courses and Co-Curricular Courses.
You may search courses offered at Ashoka here. Please use the drop down menu to choose the specific semester and subject to see the full list of courses under each department. Foundation courses are offered in all semesters and do not have prerequisites. Offerings in other categories differ in each semester. Some higher level major/minor courses may have prerequisites.
To view Summer Semester Courses-2024: Click here
We will focus on three prominent areas of decision-theoretic research: (i) theories of behavioral choices; (ii) decisions under uncertainty; and (iii) stochastic choices;
For the first topic, we will begin by setting up the foundations of rational choice theory and then look at the case against it. We will focus on a set of topics that will respond to rational choice theory’s descriptive (and at times normative) limitations. Amongst them will be prospect theory and the theme of reference-dependent preferences; sequential choice procedures featuring multiple rationales; choice theories featuring limited consideration; theories of temptation and self-control.
For the second topic, we will examine the foundations of subjective probabilities and Bayesianism. We will study the classic approaches of De Finetti, Savage, and Anscombe-Aumann to this question. After that, we will focus on the large and impressive literature on decision-making under ambiguity that has emerged in the last three decades or so. Ambiguity, here, refers to decision settings in which a decision-maker perceives “uncertainty about probability, created by missing information that is relevant and could be known” (Frisch and Baron, 1988). That such decision settings exist was pointed out by Ellsberg (1961). His work showed how ambiguity represents a normative criticism of the subjective expected utility framework of Savage (1954) and, by extension, of the Bayesian paradigm. David Schmeidler’s work in the late 1980s revived interest in this area of research. We will cover important models like Schmeidler’s Choquet expected utility, Gilboa and Schmeidler’s maximin expected utility, Klibanoff, Marinacci, and Mukerji’s smooth ambiguity model, and Siniscalchi’s vector expected utility. Before getting to all this, though, we will first look at a few landmark models of decision-making under risk like vNM expected utility and rank-dependent utility.
For the third topic, we will look at the Luce model and its generalizations, random utility and random expected utility model, and random consideration models.
