文章目录

Week2 Embedded Agents
- 2.1 Math revision
- 2.2 Accessible and inaccessible environments
- 2.3 Deterministic and non-deterministic environments
- 2.4 Static and dynamic environments
- 2.5 Formal specification of an embedded agent
- 2.6 Utility Functions
Week3:Deductive,reactive and hybrid reasoning agents
- 3.1 Deductive Agents
- - 3.1.1 Concurrent MetateM
- 3.2 Reactive Agents
- - 3.2.1 subsumption architecture
- 3.3 Hybrid Agents
Week4: Practical Reasoning Agents
- 2.1 Delibration and Means-ends reasoning
- 2.2 Resource bounded reasoning and calculative rationality
- 2.3 BDI agents
- - 2.3.1 BDI V1
  - 2.3.2 BDI V2
  - 2.3.3 BDI V3
  - 2.3.4 BDI V4 (Meta-level)
Week5: communication, coordination and cooperation
- 5.1 Communication
- - 5.1.1 KQML
  - 5.1.2 FIPA
  - 5.1.3 Social commitments
- 5.2 Cooperation
- - 5.2.1 Contract Net protocol
- 5.3 Coordinate
- - 5.3.1 Normative multi-agent systems
  - - 5.3.1.1 Prescriptive Norms
  - 5.4 Trust and reputation
  - 5.4.1 FIRE Model
Wee6: Game theory, and negotiation
- 6.1 Game Theory
- - 6.1.1 Dominant strategy
  - 6.1.2 Dominanted strategy
  - 6.1.3 Nash Equilibrium
  - 6.1.4 Pareto Optimal
  - 6.1.5 Maximising social welfare
- 6.2 Negotiation
- - - 6.2.1 Task Oriented Domains (TOD)
  - 6.2.2 Monotonic Concession Protoco
  - 6.2.3 Zeuthen strategy
Week7: Making Group Decision
- 7.1 Plurality Voting Protocol
- 7.2 Condorcet Winner
- 7.3 Linear sequential majority elections
- 7.4 Instant Runoff Voting Protocol
- 7.4 Copeland rule voting protocol
- 7.5 Borda count voting protocol
- - 7.3 Strategy-proofness
- 7.4 Gibbard-Satterthwaite Theorem
- 7.5 Weekly Pareto
- 7.6 Arrow's Theorem
- 7.7 Single Peak Preferences and Median voter rule
Week8: Allocating Scarce Resources
- 8.1 English Auction
- - 8.1.1 Shill bids
- 8.2 Dutch Auction
- - 8.2.1 Risk Averse
  - 8.2.2 Risk Seeking
- 8.3 First Price Sealed Bid Auction
- 8.4 Vickrey Auction
- 8.5 Combinatorial Auctions
- 8.6 Vickrey-Clarke-Groves mechanism(VCG)

Week2 Embedded Agents

Agents are embedded in an environment, meaning that an agent affects and is affected by the environment. An agent experiences its environment through sensors an acts on its environment through effectors.

2.1 Math revision

Power Set: The power set of a set A is the set of all subsets of A. It is written as $2^{A}$
- $A=\{x∣0<x<7$ and $x$ is odd $}\}$ . A={1,3,5} hence $2^A$ ={∅,{1},{3},{5},{1,3},{1,5},{3,5},{1,3,5}}

2.2 Accessible and inaccessible environments

An accessible environment is one in which the agent can obtain complete, accurate, up-to-date information about the environment’s state
Most moderately complex environments (including, for example, the everyday physical world and the Internet) are inaccessible.

Example:

Accessible: Chess
Inacessible: Stock market

2.3 Deterministic and non-deterministic environments

A deterministic environment is one in which every action has a single guaranteed effect — there is no uncertainty about the state that will result from performing an action.
The physical world can to all intents and purposes be regarded as non-deterministic.

2.4 Static and dynamic environments

A static environment is one in which the only changes to the environment are those caused by actions made by the agent.对环境的唯一更改是由agent执行的操作引起的更改。
A dynamic environment is one that has other processes and/or agents operating on it, and so changes in ways beyond the agent’s control. 不仅仅是有一个agent在决策，其他agents在决策时会互相影响

2.5 Formal specification of an embedded agent

$e_0, \pi>$

2.6 Utility Functions

Utility functions allow an agent to understand how “good” an outcome is.

Week3:Deductive,reactive and hybrid reasoning agents

Deductive reasoning agents, which have an explicitly model of the world represented in logical formulas and reason using logical deduction.
- Concurrent MetateM, a specific language for specifying deductive reasoning agents.
Reactive agents, which do not have an explicit model of the world that they reason with, but instead their behaviour is driven by a set of “stimulus -> action” rules.
- The subsumption architecture, probably the most well known reactive agent architecture.
Hybrid agents, which combine a purely reactive layer with higher-level reasoning layers.
- We’ll look at TouringMachines and InteRRaP as two examples of these.

3.1 Deductive Agents

3.1.1 Concurrent MetateM

E.g:

$s t u d e n t (y o u)$ $υ\upsilon$ $g r a d u a t e (y o u)$ – at some point in the future you will graduate, until then you will be a student. 直到毕业前你一直是学生

$t i t l e (m e, d r)$ $S$

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