COS3751 ASSIGNMENT 1 SOLUTIONS 2021
Question 1
(1.1) Explain the difference between a single and multi-agent environment.
An agent solving a problem by itself is a single agent environment. The key distinction is
if an agent behavior is best described as maximizing a performance measure whose value
depends on agent Ys behavior. For example in a chess game the opponent agent X is
trying to maximize its performance measure, which by the rules of chess minimizes agent
Ys performance measure. Thus chess is a competitive multi agent environment. In multi-
agent environments communication emerges as a rational behavior while non-existent in
single agent environments.
(1.2) Explain the difference between a Deterministic and Stochastic environment.
In a deterministic environment, the next state is completely determined by the current state
and the agent’s action.
In a stochastic environment, one cannot completely determine the next state based solely on
the current environment and on the agent’s actions.
(1.3) Consider a game of chess. Is this a fully observable, partially observable, or unobservable
environment? Clearly explain your answer
Fully observable, because at each point in time (each possible state) the agent’s sensors can
access the complete state of the environment. (Every single chess piece is observable).
Question 2
(2.1) List the 5 components that can be used to define a problem
1. Initial state
2. Actions
Question 1
(1.1) Explain the difference between a single and multi-agent environment.
An agent solving a problem by itself is a single agent environment. The key distinction is
if an agent behavior is best described as maximizing a performance measure whose value
depends on agent Ys behavior. For example in a chess game the opponent agent X is
trying to maximize its performance measure, which by the rules of chess minimizes agent
Ys performance measure. Thus chess is a competitive multi agent environment. In multi-
agent environments communication emerges as a rational behavior while non-existent in
single agent environments.
(1.2) Explain the difference between a Deterministic and Stochastic environment.
In a deterministic environment, the next state is completely determined by the current state
and the agent’s action.
In a stochastic environment, one cannot completely determine the next state based solely on
the current environment and on the agent’s actions.
(1.3) Consider a game of chess. Is this a fully observable, partially observable, or unobservable
environment? Clearly explain your answer
Fully observable, because at each point in time (each possible state) the agent’s sensors can
access the complete state of the environment. (Every single chess piece is observable).
Question 2
(2.1) List the 5 components that can be used to define a problem
1. Initial state
2. Actions
