Sharing design perspectives through storytelling

<span title="">2002</span> <i title="Cambridge University Press (CUP)"> <a target="_blank" rel="noopener" href="" style="color: black;">Artificial intelligence for engineering design, analysis and manufacturing</a> </i> &nbsp;
Design consists of analyzing scenarios and proposing artifacts, obeying the initial set of requirements that lead from initial to goal state. Finding or creating alternative solutions, analyzing them and sele cting the best one are expected steps on designers´ decision making process. Very often, not a sole designer, but a team of them is engaged in the design process sharing their expertise and responsibility to achieve optimum projects. In a design team, most conflicts occur due to
more &raquo; ... nding of one's assessment over specifications and contexts. Decisions explanations play a key role on teamwork success. Designers are rational agents trained to follow rational methods. Acceptable justifications lay on value function, requirements, constraints and criteria. Generally, explanations are delivered in a multimedia fashion composed of text, graphics and gestures to provide the audience the ability to perceive what was contextually imagined. The more spatial is the reasoning, the richer should be the explanation channel. This paper presents CineADD, a design explanation generation model based on cinema techniques such as: animation, scripting, editing and camera movements. The idea is to provide designers a tool for describing the way their projects should be visually explained as in a movie. Designers develop their projects on an active design document environment. Rationale is captured as a design model, so explanations can be generated instead of retrieved. The captured design model serves as a base to visually reconstruct design giving emphasis and guidance by using movie storytelling techniques. CineADD was implemented for the domain of oil pipeline layout showing the feasibility of this approach. We expect CineADD to become a commodity attachable to any Intelligent CAD system. Human-computer interaction (HCI) consists of a dialog between users with a set of demands and computer systems with a set of affordances, built in their codes, left by their designers. The interaction happens physically through input and output devices, such as keyboard and printer. It also happens through information exchange that let emerge the cognitive distinction between players. Depending on the complexity and the way messages are delivered, it may become a challenge for users to understand them. The communication involves the speaker, the listener, the channel, the content to be transmitted, the code used to make the content of a message and the message itself. Texts, graphics and pictures are the common codes employed by the computer to deliver the message. However, sometimes HCI demands an "immerse" experience [Lachman 97], as in movies, for users to efficiently perceive the overall, but sometimes hidden, information. A movie has the power to: (1) connect spatial and temporal information, (2) make concrete one's perspective of the facts and processes, (3) reconstruct human memory, and (4) make the audience think. Knowledge based systems (KBSs) have been successfully used in CAD systems to assist users in developing design projects either by offering design solutions or verifying decision alternative solutions [ten Hagen, 1987] [Garcia et al. 97]. KBSs contribute to users finding efficient solutions, given a design context. Users´ acceptance depends strongly upon the credibility of computer suggestions. An Active Design Document (ADD) [Garcia 92] is an environment for developing engineering design assisted by a computational agent trained for making decisions on projects in a specific design domain. ADD allows users to develop their project being monitored by its design agent. Whereas the agent's knowledge base covers user decisions, explanation on those decisions can be derived without user's guidance. Whenever a user's decision on a design project conflicts with ADD's expectation, the computational agent will interact with the user to gather more knowledge to improve its knowledge base. Providing clear explanation is the key to this teamwork: user and computer agent. Furthermore, since a project is generally developed in teams, the availability of design decisions explanation allows understanding of individual perspectives on design issues. Explanations vary from canned text (optionally multimedia message), working as pre-recorded annotations, to on-demand generated explanations. Although a textual explanation is fundamental, there are domains in which spatial and temporal reasoning are crucial to decision making. For such domains, explanations composed only by text, diagrams and pictures will not work because the spatial and temporal transformation will not emerge. For instance, planning a kitchen layout in a 2D (or 3D) space consists of optimizing space distribution obeying a set of norms such as the refrigerator should not be placed besides the oven. The designer's task consists of moving, erasing, and reshaping objects [Fischer & Lemke et al. 91]. The decisions in this domain are well reported neither by textual notes nor by figures. They need to be reported using actions. An event in time makes difference on possible understandings of facts. When explanations reflect a set of actions or a process in a time frame, a sequence of scenes
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1017/s0890060402163086</a> <a target="_blank" rel="external noopener" href="">fatcat:tll7bxrambff3nxrfmerj5cv3i</a> </span>
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