20 posts tagged with "vocab"

Vocabulary & Expressions​

Ontology​

Semantic Network​

• Semantic networks let us represent logical relationships visually, but their meaning remains purely logical — about objects, categories, and relations.

Tractability​

Vocabulary & Expressions​

Vocabulary & Expressions​

Knowledge Base​

• TELL, ASKS, TELL
  • TELLs the knowledge base what it preceives
  • ASKs the knowledge base what action it should perform
    • reasoning may be done about the current state of the world
    • about the outcomes of possible action sequences and so on
  • TELLs the knowledge base which action was chosen, and returns the action so that it can be executed
• MAKE-PERCEPT-SENTENCE
  • constructs a sentence asserting that the agent preceived the given percept at the given time.
• MAKE-ACTION-QUERY
  • constructs a sentence that asks what action should be done at the current time.
• MAKE-ACTION-SENTENCE
  • constructs a sentence asserting that the chosen action was executed.

Logical connectives​

BNF (Backus–Naur Form) grammar of sentences Symbols from Logic and Set Theory

• $\neg$ : negation (NOT), $\neg W_{1,3}$
  • A literal is either an atomic sentence (a positive literal) or a negated atomic sentence (a negative literal).
• $\land$ : conjunction (AND), $W_{1,3} \land P_{3, 1}$
  • its parts are the conjuncts.
• $\lor$ : disjunction (OR), $(W_{1,3} \land P_{3,1}) \lor W_{2,2}$
  • its parts are the disjuncts.
• $\implies$ : implication (IMPLIES), $(W_{1,3} \land P_{3,1}) \implies \neg W_{2,2}$
  • its premise or antecedent, and its conclusion or consequent is the part that follows the $\implies$.
  • Implications are also called rules or if-then statements.
  • Sometimes written as $\rightarrow$ or $\supset$.
• $\iff$ : biconditional (IF AND ONLY IF), $W_{1,3} \iff \neg W_{2,2}$

Truth tables​

• Logical equivalence: $P \equiv Q$:
• Validity: a sentence is valid if it is true in all models.
  • Deduction Theorem: For any sentences $\alpha$ and $\beta$, $\alpha \models \beta$ if and only if $(\alpha \implies \beta)$ is valid.
• Satisfiability: a sentence is satisfiable if it is true in, or satisfied by, some model.
• Modus Ponens: $\frac{\alpha \implies \beta, \alpha}{\therefore \beta}$
  • whenever any sentences of the form $\alpha \implies \beta$ and $\alpha$ are given, then the sentence $\beta$ can be inferred.
• And-Elimination: $\frac{\alpha \land \beta}{\therefore \alpha}$
  • from a conjunction, one of the conjuncts can be inferred.
• monotonicity: the set of entailed sentences can only increase as information is added to the knowledge base.
  • inference rules can be applied whenever suitable premises are found in the knowledge base, regardless of what other sentences are present.

Vocabulary & Expressions​

Vocabulary & Expressions​

RL​

$R(S_t,π(S_t),S_{t+1})$

시간 $t$에 상태 $S_t$에 있었고, 정책이 정한 행동 $π(S_t)$을 했더니, 다음 상태 $S_{t+1}$에 도착했다. 그때 받는 보상은 $R(S_t,π(S_t),S_{t+1})$이다.

• 현재 상태에서 정책이 정한 행동을 취해 다음 상태로 갔을 때 받은 보상
• $S_t$: 시간 $t$에 에이전트가 위치한 현재 상태
• $π(S_t)$: 정책 π가 현재 상태 $S_t$에서 선택한 행동 (action)
• $S_{t+1}$: 그 행동을 수행한 뒤 도달한 다음 상태
• $R$: 이 세 가지 (현재 상태, 행동, 다음 상태)에 의해 결정되는 보상 함수

Passive RL​

• Direct Utility Estimation
• ADP (Adaptive Dynamic Programming)
• TD (Temporal Difference Learning)

Vocabulary & Expressions​

Vocabulary & Expressions​

Vocabulary & Expressions​

Vocabulary & Expressions​

Agents​

• Simple reflex agents
• Model-based reflex agents
• Goal-based agents
• Utility-based agents

Vocabulary & Expressions​