Sequential contributions

A distinctively different interaction protocol would be one that is based on sequential contributions, implying the generation of plan proposals by having initiators request and process the claims for the different land uses one by one, instead of all at the same time. An initiator then intends to reach agreement over the assignments with a selected participant before turning to the next. In this setting, participants only become involved in the process at the time the initiator requests for their subsequent contributions. Hence, the relative importance the initiator gives to the various land uses is not only embedded in its assignment strategy but also, and more obviously, in the order in which he or she calls upon the participants.

In comparison with the interaction protocol of simultaneous contributions, the process differs regarding two aspects (Figure 5-8). First, there is an obvious difference in step 1, when the initiator uses the current future state belief, Bel{SAF}, to value the importance of the different remaining contributions from the viewpoint of his or her own land use in order to determine the order-of-turns to apply in the process. He or she then sends the Bel{SAF} to the participant-at-turn, requesting that agent’s claims. Second, acting in accordance to the current stage of the process in step 5 implies that the initiator checks whether or not there are other participants remaining when the assignments for the participant-at-turn are completely finalized. When there are, the initiator goes back to step 1 in order to call upon the next participant, with the assignments forming the new

Bel{SAF}. In the case of having received a notice of rejection from the participant-at-turn while still other participants remain, the rejecting agent will be put in a ‘suspended mode’ and contacted after reaching agreement with a following participant. This is according to

the notion that agreement over the assignments can still be reached at that later stage, when the rejecting participant becomes aware that it might be necessary to lower its satisfaction threshold for the sake of common interests. At the moment that the last suggested assignments were completely finalized for all land uses, there will be no participants remaining and the initiator will see whether they all accepted. If so, the plan proposal has been drawn up successfully. If not, the initiator has to find other ways to acquire a completed plan proposal (section 5.4.1).

Claim Strategy Assignment Strategy CLAIMS ASSIGNMENTS Assessment of Assignments Satisfied? Goal State Belief PLAN PROPOSAL Future State Belief All assignments finalized? NO YES Try differently Send Assignments Send Belief Return “acceptance” Return Claims

Return “rejection” Final round? NO

YES NO YES Collective completion? Finalization of Assignments NO YES NO 1. 2. 3. 4. 5. Select Participant Any rejections? Next Participant? YES NO YES * including initiator

5.5 CONCLUSIONS

Whereas multi-agent technology has already been widely acknowledged as a powerful tool for simulating space-time phenomena that emerge from the behaviours of individuals, households, firms, organizations, and so on, it is rather surprising to observe that attempts to further exploit the technology within the context of PSS remain limited in number even though the potential applications seem rather evident (section 3.2). Recalling the two principal requirements for PSS (section 2.2.2), there is a fundamental and instant need for finding ways in which the generation of alternative plans can be supported equally well as the subsequent evaluation of these plans. Furthermore, the crucial role of specialized knowledge in planning decision-making asks for flexible and intelligent means to incorporate expertise over a range of disciplines. An appropriate solution may be found in the utilization multi-agent technology that, through its concepts of anthropomorphy and modularity, makes it possible to represent the individual experts inside an urban planning team, give direct access to the specialized knowledge of these experts and provide the opportunity to simulate the interactive decision-making within an urban planning team for both generating and evaluating alternative plans. The addition of this ‘layer of agents’ (section 3.3.2) would bring PSS an important step closer to a complete representation of the urban system and, thus, provide planning practitioners with more powerful support in performing their professional tasks.

This chapter has specified a multi-agent model dedicated to the generation of alternative plans in order to draw attention to the opportunity of having multi-agent technology support this more creative Design phase of planning as well, supplementary to its apparently most obvious application in the Choice phase to serve forecasting and evaluation purposes (section 4.2). Without a doubt, variations on the presented model can come to one’s mind, as well as further enhancements. Considering the novelty of this type of model, however, it can be considered equally important to allow demonstration and testing of the model in order to highlight the characteristics that make it different from conventional multi-agent applications in planning. For that reason, the next chapter will discuss the design and implementation of the model into a prototype application, after which an extensive series of tests is conducted to examine the properties of the model.

PART III