Multi-agent technologies are being used in many real-world applications and their number is steadily increasing; examples of such domains are smart grids, transportation systems, as well as search and rescue tasks. On one hand, this requires to develop appropriate formal foundations of multi-agent systems, and on the other hand, to tailor existing theories to become (computationally) applicable and understandable to non-experts that are primarily interested in using multi-agent technologies and to a lesser extent in the underlying theories. In particular, this holds for theories concerned with key characteristics of agents: decision making and cooperation. That is, agents’ ability to take decisions in an autonomous (and often intelligent) manner and to possibly cooperate with others. Agents need to decide which action to execute, which plans to follow, with whom to cooperate, and which goals to pursue. Often, in order to take good decisions the behaviour of other agents has to be taken into account.
Multi-agent decision making (MADM) is complex and has many facets. Game theory is among the -if not the most- prominent tool to model and to analyse decision making in multi-agent systems. It is a mathematical tool to analyse the interactions between rational players, as such it is an idealised abstraction of how decision making in many existing multi-agent applications takes place. In many applications agents need to communicate and coordinate with others and with humans. Therefore, concrete methods are needed which allow agents to work together, to reason strategically, and to make agreements.
In this tutorial we discuss multi-agent decision making from a theoretical and from a more practical perspective. First, we briefly introduce game theory as a basic tool to analyse multi-agent decision making and to predict agents’ behaviour. We discuss cooperative as well as competitive settings and touch upon formal tools to reason about abilities of agents. Then, we emphasize on the need to coordinate decisions and behaviours, in particular, in the setting of human agent teamwork. In many real world problems decision making is not a one-shot process, as is the case in normal form games, but an interactive process; therefore, we discuss a selection of mechanisms that allow agents to reach agreements interactively and which can be used in applications. Finally, we also explain how decisions of autonomous agents can be controlled and influenced.
- classical decision making and multi agent decision making
- brief introduction to game theory
- reasoning about cooperation (strategic logics)
- human-agent teamwork
- communication and coordination
- reaching agreements interactively: negotiation mechanisms
- controlling and influencing decisions (e.g. normative systems)