This chapter gives various applications of the theory developed in the previous chapters. The first application is a proof of generation of mouse full pointclasses assuming Strong Mouse Capturing. The second application is a proof that Strong Mouse Capturing holds in the minimal model of LSA; so the Mouse Set Conjecture is true in all models of AD^+ up to the minimal model of LSA. The third application is a proof of consistency of LSA from the existence of a Woodin limit of Woodin cardinals.

This chapter analyzes HOD up to $\Theta$ in the minimal model of LSA under the assumption that Strong Mouse Capturing (SMC) holds.

This chapter covers:

1. • How a well-designed robot can lift interactions to the next level (physical design);

2. • How people do not treat robots as an assembly of plastic, electronics, and code but rather as humanlike entities (anthropomorphism);

3. • How HRI research draws on psychological theories, such as anthropomorphism, to design and study people’s interactions with robots;

4. • Design methods and prototyping tools used in human–robot interaction.

About this book; Christoph Bartneck; Tony Belpaeme; Friederike Eyssel; Takayuki Kanda; Merel Keijsers; Selma Šabanović; Notes on second edition

This chapter covers:

1. • The diverse areas of robot applications where human–robot interaction (HRI) is an important component;

2. • Applications beyond robots that are studied in a research context;

3. • Possible future applications;

4. • Potential problems that would need to be solved when HRI has a larger role in our society.

The main purpose of this chapter is to isolate the definition of short tree strategy mice. The main problem with defining this concept is the fact that it is possible that maximal iteration trees (which should not have branches indexed in the strategy predicate) may core down to short iteration trees (which must have branches indexed in the strategy predicate), thus causing indexing issues. To resolve this issue we will design an authentication procedure which will carefully choose iteration trees and index their branches. Thus, if some iteration tree doesn’t have a branch indexed in the strategy predicate then it is because the authentication procedure hasn’t yet found an authenticated branch, and therefore, such iteration trees cannot core down to an iteration tree whose branch is authenticated.

This chapter introduces the main concepts and the problems to be investigated by the book. In particular, the chapter defines the Largest Suslin Axiom (LSA) and the minimal model of LSA. The chapter summarizes the main theorems to be proved in the book: HOD of the minimal model of LSA satisfies the Generalized Continuum Hypothesis, the Mouse Set Conjecture holds in the minimal model of LSA, the consistency of LSA from large cardinals, the consistency of LSA from strong forcing axioms like PFA.

The main goal of this chapter is to prepare some terminology to be used in the rest of the book. One important notion introduced in this chapter is that of the undropping game. We will use it to prove a comparison theorem for hod mice in Chapter 4.

This chapter covers:

1. • The difference between affect, emotions, and mood;

2. • What roles emotions play in interacting with other humans and robots;

3. • Basic models of emotions;

4. • The challenges in emotion processing.

This chapter covers:

1. • The basic hardware and software components that a robot consists of;

2. • The techniques we can apply to make a robot ready for interacting with people.

This chapter covers:

1. • Current attitude of the general public toward robots and how this may change in the coming years;

2. • Possible shifts and developments in the nature of human–robot relationships, specifically companion bots;

3. • Further development of the technology of human–robot interactions, specifically artificial intelligence;

4. • The inherent issues with predicting the future (“crystal ball problems”).

This chapter studies internal theory of lsa hod mice. Suppose $(\mathcal{P},\Sigma)$ is a hod pair of an sts hod pair, $X$ is a self-wellordered set such that $\mathcal{P}\in X$, and $\mathcal{N}$ is a $\Sigma$ or $\Sigma$-sts mouse over $X$. The main theorem of this chapter shows that N is $\Sigma$-closed and has fullness preserving iteration strategy, then $\Sigma \restriction \mathcal{N}[g]$ is definable in $\mathcal{N}[g]$ for any generic $g$ over $\mathcal{N}$ . The main idea behind the proof is that the branch of an iteration tree $\mathcal{T}$ on $\mathcal{P}$ can be identified by the authentication process introduced in Chapter 3.