Iran Is Using Tiny'Mosquito' Boats to Shut Down the Strait of Hormuz Iran's traditional naval fleet has been almost completely destroyed by US-Israeli raids. But Iran's Revolutionary Guard has deployed a fleet of small vessels that is crippling every passageway. In the Strait of Hormuz, Iran has developed an asymmetrical naval strategy that is crippling the passage of container ships. This "hemostat" uses guerrilla tactics, after Iran's "traditional" fleet was almost entirely destroyed by US and Israeli attacks. No longer able to rely on specialized military ships, Tehran is using an unconventional force made up of dozens of small military vessels armed with missiles, machine guns, and drones.

This paper presents the first results of the research into AI-based support of the room configuration process during the early design phases in architecture. Room configuration (also: room layout or space layout) is an essential stage of the initial design phase: its results are crucial for user-friendliness and success of the planned utilization of the architectural object. Our approach takes into account different possible actions of the configuration process, such as adding, removing, or (re)assigning of the room type. Its mode of operation is based on specific process chain clusters, where each cluster represents a contextual subset of previous configuration steps and provides a recurrent neural network trained on this cluster data only to suggest the next step, and a case base that is used to determine if the current process chain belongs to this cluster. The most similar cluster then tries to suggest the next step of the process. The approach is implemented in a distributed CBR framework for support of early conceptual design in architecture and was evaluated with a high number of process chain queries to prove its general suitability.

In this paper, we present RALE-ACL, a communication language for case-based agents in multi-agent systems (MAS) that utilize case-based reasoning (CBR) as the main means of decision making for their agents. RALE-ACL is an accompanying approach of RALE-CBR, a methodology for construction of CBR-based approaches and systems that adds more flexibility to the classic 4R cycle of case-based reasoning. The main goal of RALE-ACL is to establish a much more CBR-compatible alternative to the KQML and FIPA-ACL-based languages, that are currently used in many multi-agent systems, but are too generic and therefore only cumbersomely usable for the specific structure and purposes of case-based agents. This paper is the final part in the trilogy about the RALE methodology.