Week 1 Flashcards
1
Q
Definitions of artificial intelligence organized into four categories?
A
- Thinking Humanly, aktivitas yang diasosiasikan dengan pemikiran manusia seperti decision-making, problem solving, learning. etc.
- Acting Humanly, pembelajaran bagaimana membuat komputer melakukan hal-hal dimana, pada saat ini, manusia lebih baik.
- Thinking Rationally, pembelajaran dari komputasi yang membuat hal seperti mempersepsikan, beralasan, dan bertindak menjadi nyata.
- Acting Rationally, pembelajaran dari mendesain intelligent agents.
2
Q
Foundations of AI?
A
Philosophy Mathematics Economics Neuroscience Psychology Computer Engineering Control Theory Linguistics
3
Q
Agent Types?
A
- Reflex agents
- Reflex agents with internal states
- Goal-based agents
- Utility-based agents
- Learning agents
4
Q
Nature of environment?
A
- Fully observable vs. partially observable
- Single agent vs. multiagent
- Deterministic vs. stochastic
- Episodic vs. sequential
- Static vs. dynamic
- Discrete vs. continuous
- Known vs. unknown
5
Q
What is PEAS?
A
Performance, Environment, Actuators, Sensors
6
Q
Concept of rationality?
A
- Goals
- Percepts
- Sensors
- Effectors
- Actions
- Environment
7
Q
Karakteristik dari Agent?
A
- agents are autonomous, that is, they act on behalf of the user
- agents contain some level of intelligence, from fixed rules to learning engines that allow them to adapt to changes in the environment
- agents don’t only act reactively, but sometimes also proactively
- agents have social ability, that is, the communicate with the user, the system and other agents as required
- agents may also cooperate with other agents to carry out more complex tasks than they themselves can handle
- agents may migrate from one system to another to access remote resources or even to meet other agents
8
Q
Agent types?
A
- Reflex agents
- Reflex agents with internal states
- Goal-based agents
- Utility-based agents
9
Q
Rational action?
A
the action that maximizes the expected value of the performance measure given the percept sequence to date
10
Q
Uninformed search strategies?
A
- Breadth-first search
expands the shallowest nodes first; it is complete, optimal for unit step costs, but has exponential space complexity - uniform-cost search
expands the node with lowest path cost, g(n), and is optimal for general step costs - Depth-first search
expands the deepest unexpanded node first. It is neither complete nor optimal, but has linear space complexity. - depth-limited search
- iterative deepening search
calls depth-virst search with increasing depth limits until a goal is found. - Bidirectional search