Multi-agent systems often communicate to perform better at their tasks. However, messages sometimes get lost after sending, and the communication is disrupted. This paper looks into the effects of messages having a chance of not arriving with an agent using the Blocks World for Teams simulation environment. The environment uses agent teams written in the GOAL programming language. First, this thesis details a pilot using existing agent teams with different communication failure models. Each agent team is run multiple times per failure model to get preliminary data. Based on this data, the thesis goes into a followup experiment. The experiment starts with the design of four agent teams, which only differ in the communication strategy they use to share information. What follows is the configuration of Blocks World for Teams, agent team size selection, the communication failure model, how the simulations are are run in a consistent manner, and finally, how the data generated by the simulations is processed. After modifying the agent teams, so they no longer waste limited resources, the experiment is repeated. The different communication strategies are affected to different degrees by communication failure. While the teams perform better than a single agent without failure, slowdown with communication failure can make the teams perform worse than the single agent. How often agents obstruct each other does not appear to be affected by how often communication fails as long as it does fail.

There has been a big increase in the use of social robots, such as Pepper, which use verbal communication as the main method of interacting with a human. Verbal communication with a robot is performed using Automatic Speech Recognition (ASR) to recognize words from an audio stream containing speech.
These social robots are being more frequently used in noisy environments.
As such, this thesis investigates 1) whether Pepper's built-in keyword spotter can be replaced by an ASR system able to recognize continuous speech in Dutch; 2) whether Pepper's ASR pipeline can be made more robust against noise, without changing its hardware.
To that end, Pepper's built-in keyword spotter and Sound Source Localization (SSL) algorithm are evaluated against an ASR pipeline based on a Delay-and-Sum beamformer, MUSIC Sound Source Localization, and Google Cloud Speech-to-Text.

The proposed pipeline showed a significant decrease in Keyword Error Rate of 6.2\% compared to Pepper's built-in keyword spotter, and a significant decrease of Word Error Rate (WER) of 21.4\% on Dutch continuous speech in clean listening conditions. A decrease in WER of 13.3\% was observed in an SNR of 8 dB, and a decrease in WER persisted throughout lower Signal-to-Noise ratios (SNR).

As such, it has been shown that Pepper's speech recognition can be improved and made more robust against noise by preprocessing the audio using MUSIC SSL and a Delay-and-Sum beamformer, and transcribing the speech (in Dutch) using Google Cloud Speech-to-Text.

In order to be accepted by negotiating parties, negotiation protocols need to be fair and unbiased. We extend the bilateral turn-taking negotiation protocol to multiparty multilateral turn-taking peer negotiation protocols maintaining its fairness properties. We define the de- sign space of such protocols and capture the design decisions that go into creating them. We use this design space to introduce two novel protocols adhering to the fairness prop- erties: Stacked Alternating Offer Protocol (SAOP) and Alternating Multi-offer Consensus Protocol (AMCP). A method for measuring speed and social welfare properties of multi- party multilateral turn-taking peer negotiation protocols is introduced and used to evaluate SAOP and AMCP using automated negotiation agents from the Automated Negotiation Agent Competition (ANAC). We show that against our expectations, the agents prefer to use the more complex AMCP protocol. Both protocols are usable in automated, human, and hybrid negotiations. The design space enables more informed design decisions when creating protocols and lays the foundation for further studies in finding desirable protocol properties that in turn improve the quality of the negotiation outcome.